U.S. patent application number 16/742673 was filed with the patent office on 2020-08-06 for washing machine and method for controlling the same.
The applicant listed for this patent is LG ELECTRONICS INC.. Invention is credited to Byungkeol Choi, Sungmok Hwang, Dongsoo KANG, Jinyoung Park, Hyunseok Seo.
Application Number | 20200248354 16/742673 |
Document ID | / |
Family ID | 1000004640403 |
Filed Date | 2020-08-06 |
![](/patent/app/20200248354/US20200248354A1-20200806-D00000.png)
![](/patent/app/20200248354/US20200248354A1-20200806-D00001.png)
![](/patent/app/20200248354/US20200248354A1-20200806-D00002.png)
![](/patent/app/20200248354/US20200248354A1-20200806-D00003.png)
![](/patent/app/20200248354/US20200248354A1-20200806-D00004.png)
![](/patent/app/20200248354/US20200248354A1-20200806-D00005.png)
![](/patent/app/20200248354/US20200248354A1-20200806-D00006.png)
![](/patent/app/20200248354/US20200248354A1-20200806-D00007.png)
![](/patent/app/20200248354/US20200248354A1-20200806-D00008.png)
![](/patent/app/20200248354/US20200248354A1-20200806-D00009.png)
![](/patent/app/20200248354/US20200248354A1-20200806-D00010.png)
View All Diagrams
United States Patent
Application |
20200248354 |
Kind Code |
A1 |
KANG; Dongsoo ; et
al. |
August 6, 2020 |
WASHING MACHINE AND METHOD FOR CONTROLLING THE SAME
Abstract
The present disclosure relates to a washing machine having a
tub, a vibration sensor provided at the tub, a drum accommodating
laundry therein and provided to be rotatable in the tub, and a
controller configured to measure a value regarding multi-axis
vibration occurring in the tub with the vibration sensor at a
detection section in which the drum rotates at a specific
rotational speed during a dewatering process, determine a predicted
value of maximum vibration displacement expected to be generated in
the tub based on the measured value, and determine whether to
initialize the dewatering process at the detection section based on
the determined predicted value of the maximum vibration
displacement and a predetermined reference value.
Inventors: |
KANG; Dongsoo; (Seoul,
KR) ; Park; Jinyoung; (Seoul, KR) ; Seo;
Hyunseok; (Seoul, KR) ; Choi; Byungkeol;
(Seoul, KR) ; Hwang; Sungmok; (Seoul, KR) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
LG ELECTRONICS INC. |
Seoul |
|
KR |
|
|
Family ID: |
1000004640403 |
Appl. No.: |
16/742673 |
Filed: |
January 14, 2020 |
Current U.S.
Class: |
1/1 |
Current CPC
Class: |
D06F 23/02 20130101;
D06F 33/48 20200201; D06F 2103/26 20200201; D06F 33/40 20200201;
D06F 2105/62 20200201; D06F 34/16 20200201; D06F 2105/48
20200201 |
International
Class: |
D06F 33/40 20200101
D06F033/40; D06F 33/48 20200101 D06F033/48; D06F 34/16 20200101
D06F034/16; D06F 23/02 20060101 D06F023/02 |
Foreign Application Data
Date |
Code |
Application Number |
Feb 1, 2019 |
KR |
10-2019-0014059 |
Claims
1. A washing machine, comprising: a tub; a vibration sensor
disposed at the tub; a drum that is rotatable and disposed inside
the tub, the drum being configured to accommodate laundry therein;
and a controller, wherein the controller is configure to: measure a
value regarding multi-axis vibration occurring in the tub with the
vibration sensor at a detection section in which the drum rotates
at a specific rotational speed during a dewatering process,
determine a predicted value of maximum vibration displacement
expected to be generated in the tub based on the measured value,
and determine whether to initialize the dewatering process at the
detection section based on at least the determined predicted value
of the maximum vibration displacement and a predetermined reference
value.
2. The washing machine of claim 1, wherein the vibration sensor
measures a plurality of vibration displacement values for a
plurality of vibrations occurring along a plurality of different
axes with respect to the tub.
3. The washing machine of claim 2, wherein the controller
calculates information of a plurality of phase differences between
the plurality of vibrations.
4. The washing machine of claim 3, wherein the information of the
plurality of phase differences comprises information regarding
phase differences between any one of the plurality of vibrations
and the remaining vibrations.
5. The washing machine of claim 3, wherein the controller outputs
the predicted value of the maximum vibration displacement as an
output value by inputting at least one of the plurality of
vibration displacement values, the information of the plurality of
phase differences, and a rotational speed variation value as an
input value of a pre-trained Artificial Neural Network (ANN).
6. The washing machine of claim 1, wherein the predicted value of
the maximum vibration displacement comprises a plurality of
predicted values of maximum vibration displacement expected to be
generated in each of a plurality of different axes.
7. The washing machine of claim 6, wherein the controller controls
the drum to rotate faster than a specific rotational speed of the
detection section when all of the plurality of predicted values of
the maximum vibration displacement are equal to or less than the
predetermined reference value.
8. The washing machine of claim 6, wherein the controller controls
the drum to stop rotation of the drum at the detection section when
at least one of the plurality of predicted values of the maximum
vibration displacement exceeds the predetermined reference
value.
9. The washing machine of claim 1, wherein the predetermined
reference value is set according to each of a plurality of
different axes.
10. The washing machine of claim 1, wherein the specific rotational
speed is faster than a speed of the drum rotating while the laundry
is compressed against a wall surface of the drum, and the
rotational speed is slower than a maximum rotational speed of the
dewatering process.
11. A method for controlling a washing machine, the method
comprising: measuring, via a controller, a value regarding
multi-axis vibration occurring in a tub that includes a drum with a
vibration sensor at a detection section in which the drum rotates
at a specific rotational speed during a dewatering process;
determining, via the controller, a predicted value of maximum
vibration is displacement expected to be generated in the tub based
on the measured value; and determining, via the controller, whether
to initialize the dewatering process at the detection section based
on the determined predicted value of the maximum vibration
displacement and a predetermined reference value.
12. The method of claim 11, wherein a plurality of vibration
displacement values are measured, via the vibration sensor, for a
plurality of vibrations occurring along a plurality of different
axes with respect to the tub.
13. The method of claim 12, wherein the measuring is configured to
calculate information of a plurality of phase differences between
the plurality of vibrations.
14. The method of claim 13, wherein the information of the
plurality of phase differences includes information regarding phase
differences between any one of the plurality of vibrations and the
remaining vibrations.
15. The method of claim 13, wherein the determining is configured
to output the predicted value of the maximum vibration displacement
as an output value by inputting at least one of the plurality of
vibration displacement values, the information of the plurality of
phase differences, and a rotational speed variation value as an
input value of a pre-trained Artificial Neural Network (ANN).
16. The method of claim 11, wherein the predicted value of the
maximum vibration displacement includes a plurality of predicted
values of maximum vibration displacement expected to be generated
in each of a plurality of different axes.
17. The method of claim 16, further comprising rotating the drum
faster than a specific rotational speed of the detection section
when all of the plurality of predicted values of the maximum
vibration displacement are equal to or less than the predetermined
reference value.
18. The method of claim 16, wherein the determining whether to
initialize the dewatering process is configured such that the
dewatering process is initialized by stopping rotation of the drum
at the detection section when at least one of the plurality of
predicted values of the maximum vibration displacement exceeds the
predetermined reference value.
19. The method of claim 11, wherein the predetermined reference
value is set according to each of a plurality of different
axes.
20. The method of claim 11, wherein the specific rotational speed
is faster than a speed of the drum rotating while the laundry is
compressed against a wall surface of the drum, and the specific
rotational speed is slower than a maximum rotational speed of the
dewatering process.
Description
CROSS-REFERENCE TO RELATED APPLICATION
[0001] Pursuant to 35 U.S.C. .sctn. 119(a), this application claims
the benefit of Korean Patent Application No. 10-2019-0014059, filed
on Feb. 1, 2019, the contents of which is incorporated by reference
herein in its entirety.
BACKGROUND
1. Technical Field
[0002] The present disclosure relates to a washing machine and a
method for controlling the washing machine. More particularly, the
present disclosure relates to a washing machine that predicts
excessive vibration expected to be generated in a dewatering
process based on machine learning, and a method for controlling the
washing machine.
2. Description of the Related Art
[0003] A washing machine is a device used to remove dirt from
laundry (hereinafter also referred to as "fabric"), such as
clothing, bedding, etc. by using chemical cleaning action of water
and a detergent, and physical action such as friction between water
and the laundry.
[0004] A washing machine is classified into an agitator type, a
pulsator type, and a drum type. The drum type washing machine
includes a water storage tank (or tub) for storing water and a
washing tub (or drum) rotatably disposed in the water storage tank
to accommodate laundry therein.
[0005] The washing tub (or drum) is formed with a plurality of
through holes through which water passes. A washing operation is
generally divided into a washing stroke (cycle), a rinsing stroke
(cycle) and a dewatering stroke (cycle). A process of each stroke
may be displayed through a control panel (or display) provided
outside a washing machine.
[0006] The washing stroke removes dirt from laundry using friction
between water stored in the water storage tank and the laundry in
the washing tub, and chemical cleaning action of a detergent in
water.
[0007] The rinsing stroke rinses the laundry with clean water to
remove the detergent adhered to the laundry by supplying clean
water (no detergent dissolved) into the water storage tank. A
fabric softening agent may be supplied together with the water
during the rinsing stroke.
[0008] The dewatering stroke removes water from the laundry by
rotating the washing tub at high speed after the rinsing stroke is
finished. Normally, the washing operation of the washing machine is
completed after the dewatering stroke. However, in the case of a
combo washer dryer, a drying stroke (cycle) may be occur after the
dewatering stroke.
[0009] Normally, the washing operation is set to operate under a
different condition depending on a load or amount of laundry
(hereinafter also referred to as "amount of fabrics" or "amount of
laundry") located in the washing tub. For example, a water level,
washing strength, a drain time, a dewatering time, etc., may vary
according to the amount of laundry.
[0010] In the washing operation, washing is performed as laundry is
dropped within the washing tub by the force of gravity while the
drum rotates with respect to a forward-backward direction when
viewed from the front side of the washing machine.
[0011] In the dewatering operation, the drum is accelerated to a
higher rotational speed. Then, by a centrifugal force, water from
the laundry adhered to the drum is discharged to the tub through
dewatering holes on a surface of the drum.
[0012] During the dewatering process, when the load of laundry in
the drum is unevenly distributed, unbalance (hereinafter, "UB")
occurs, which causes a drive unit (a tub that includes a drum) to
vibrate due to gravity. This vibration is transferred to the tub, a
cabinet and the floor, and causes noise. In addition, a load
required to rotate the drum is increased.
[0013] Accordingly, as for the washing machine, reducing vibration
of the drum is important in terms of both product stability and
customer satisfaction.
[0014] In the conventional art, in order to reduce vibration of a
drive unit, a balancing unit (ball balancer, liquid balancer), or
the like is used to proactively reduce UB itself. This increases
the weight of the drive unit as a way of being less affected by UB.
In addition, a technology for reducing vibration of the drive unit
using a friction damper and a spring having a damping force has
been developed.
[0015] Korean Patent Application No. 10-0244874, which is hereby
incorporated by reference, discloses a configuration for predicting
vibration expected to occur so as to remove unbalance in a washing
machine. In that publication, transient vibration is predicted by
reading a voltage waveform output from a gyro sensor, and
calculating a surface integral of the voltage waveform to determine
unbalance of laundry, and then comparing the determined unbalance
with a reference value, which is a criterion for determining an
occurrence of transient vibration. An amount of eccentricity (UB
value) is only compared with a reference value (reference UB value)
of generated transient vibration to predict whether or not
transient vibration will occur based on the compared amount of
eccentricity (UB value). In other words, the amount of eccentricity
rather than a vibration value is used for predicting transient
vibration, and a predicted value of transient vibration (i.e., a
maximum transient vibration value) is not accurately calculated.
Accordingly, prediction accuracy for occurrence of transient
vibration is not sufficiently reliable. This may result in an
unnecessary stop (or initialization) of the dewatering process
occurs, leading to an increase in a dewatering time.
[0016] Korean Patent Application No. 10-1272341, which is hereby
incorporated by reference, discloses a configuration for measuring
RPM fluctuations (UB value) and an actual amount of vibration
generated in a washing machine. If the detected amount of vibration
is greater than a reference vibration amount, or the detected RPM
fluctuations are greater than reference RPM fluctuations, rotation
of a motor is stopped to perform a process of evenly distributing
laundry again. An amount of vibration actually generated is only
compared with a reference vibration amount. This fails to predict
(calculate) a vibration value of transient vibration expected to be
generated (i.e., the maximum transient vibration value) by using
the amount of vibration actually generated. A configuration for
accurately predicting (calculating) a transient vibration value is
not disclosed, thereby lowering prediction accuracy for occurrence
of transient vibration. This causes an unnecessary stop (or
initialization), and thus, time required for dewatering is
increased.
[0017] The conventional machine learning is focused on
statistics-based classification, regression, and cluster models. In
particular, in supervised learning of the classification and
regression models, the learning models that distinguish new data
from characteristics of learning data based on these
characteristics are defined by a person in advance. The deep
learning, on the other hand, is one in which a computer searches
for and identifies characteristics of learning data.
[0018] One of the factors that accelerated development of the deep
learning is deep learning frameworks provided as an open source.
Theano of the University of Montreal, Canada, Torch of New York
University, Caffe of the University of California, Berkeley, and
TensorFlow of Google are the examples of the deep learning
frameworks.
[0019] With the release of deep learning frameworks, in addition to
deep learning algorithms, extraction and selection of data used for
a learning process, a learning method, and learning are becoming
more important for effective learning and recognition.
[0020] Also, research is being actively conducted for applying AI
and machine learning to various products and services.
[0021] In addition, development for employing AI and machine
learning in a dewatering cycle is being actively carried out to
perform the optimized dewatering cycle.
[0022] For example, Korean Patent Application No. 10-1841248, which
is hereby incorporated by reference, discloses a configuration for
detecting a load or amount of laundry by inputting a rotational
speed of a motor as an input value as an Artificial Neural Network
(ANN). However, this reference does not teach or disclose a
configuration that uses a pre-trained ANN to detect a maximum
transient vibration value (or a predicted value of the maximum
vibration displacement) expected to be generated in a dewatering
process.
SUMMARY
[0023] The present disclosure solves at least the above-identified
problems.
[0024] An aspect of the present disclosure is to provide a washing
machine that decreases the time required for dewatering by
accurately predicting an occurrence of excessive vibration, and a
method for controlling the washing machine.
[0025] Another aspect of the present disclosure is to provide a
washing machine that accurately detects unbalance (UB) that causes
excessive vibration in a dewatering process, and a method for
controlling the washing machine.
[0026] Still another aspect of the present disclosure is to provide
a washing machine that predicts an occurrence of excessive
vibration in a dewatering process at an early stage of the
dewatering process using an Artificial Neural Network (ANN), and a
method for controlling the washing machine.
[0027] Still another aspect of the present disclosure is to provide
a washing machine that prevents a dewatering time from being
prolonged due to unnecessary initialization of a dewatering process
by accurately determining whether to initialize the dewatering
process before excessive vibration occurs, and a method for
controlling the washing machine.
[0028] Still another aspect of the present disclosure is to provide
a washing machine that directly calculates a predicted value of the
maximum vibration displacement to be generated in a dewatering
process using a vibration value measured by a vibration sensor and
accurately determining an occurrence of excessive vibration based
on the predicted value of the maximum vibration displacement, and a
method for controlling the washing machine.
[0029] The tasks to be solved in the present disclosure may not be
limited to the aforementioned, and other problems to be solved by
the present disclosure will be obviously understood by a person
skilled in the art based on the following description.
[0030] The embodiments disclosed herein provide a washing machine
that may include a controller configured to measure a value
regarding multi-axis vibration with a vibration sensor at a
detection section in which a drum rotates at a specific rotational
speed (i.e., a low RPM section) so as to reduce time required for
dewatering, determine a predicted value of maximum vibration
displacement expected to be generated in an entire dewatering
process (or resonance section (or transient section)) based on the
measured value, and determine to initialize the dewatering process
at the detection section (low RPM section) when the predicted value
of the maximum vibration displacement exceeds a predetermined
reference value.
[0031] The embodiments disclosed herein also provide a washing
machine that may include a controller capable of accurately
detecting a predicted value of maximum vibration displacement
expected to be generated in an entire dewatering process (or
resonance section (or transient section) of 150 to 600 RPM) by
inputting a value regarding multi-axis vibration into an Artificial
Neural Network (ANN) pre-trained or learned through machine
learning as an input value to accurately determine whether to
initialize the dewatering process.
[0032] The embodiments disclosed herein further provide a washing
machine that may include a tub, a vibration sensor provided at the
tub, a drum accommodating laundry therein and provided to be
rotatable in the tub, and a controller configured to measure a
value regarding multi-axis vibration occurring in the tub with the
vibration sensor at a detection section in which the drum rotates
at a specific rotational speed during a dewatering process,
determine a predicted value of maximum vibration displacement
expected to be generated in the tub based on the measured value,
and determine whether to initialize the dewatering process at the
detection section based on the determined predicted value of the
maximum vibration displacement and a predetermined reference
value.
[0033] According to an embodiment disclosed herein, the vibration
sensor may measure a plurality of vibration displacement values for
a plurality of vibrations occurring along a plurality of different
axes with respect to the tub.
[0034] According to an embodiment disclosed herein, the controller
may calculate information of a plurality of phase differences
between the plurality of vibrations.
[0035] According to an embodiment disclosed herein, the information
of the plurality of phase differences may include information
regarding phase differences between any one of the plurality of
vibrations and the remaining vibrations.
[0036] According to an embodiment disclosed herein, the controller
may output the predicted value of the maximum vibration
displacement as an output value by inputting at least one of the
plurality of vibration displacement values, the information of the
plurality of phase differences, and a rotational speed variation
value as an input value of a pre-trained Artificial Neural Network
(ANN).
[0037] According to an embodiment disclosed herein, the predicted
value of the maximum vibration displacement may include a plurality
of predicted values of maximum vibration displacement expected to
be generated in each of a plurality of different axes.
[0038] According to an embodiment disclosed herein, the controller
may rotate the drum faster than a specific rotational speed of the
detection section, when all of the plurality of predicted values of
the maximum vibration displacement are equal to or less than the
predetermined reference value.
[0039] According to an embodiment disclosed herein, the controller
may stop rotation of the drum at the detection section, when at
least one of the plurality of predicted values of the maximum
vibration displacement exceeds the predetermined reference
value.
[0040] According to an embodiment disclosed herein, the
predetermined reference value may be set according to each of a
plurality of different axes.
[0041] According to an embodiment disclosed herein, the specific
rotational speed may be faster than a speed of the drum rotating
while the laundry is attached to a wall surface of the drum, and
slower than a maximum rotational speed of the dewatering
process.
[0042] The embodiments disclosed herein also provide a method for
controlling a washing machine that may include measuring a value
regarding multi-axis vibration occurring in a tub that includes a
drum with a vibration sensor at a detection section in which the
drum rotates at a specific rotational speed during a dewatering
process, determining a predicted value of maximum vibration
displacement expected to be generated in the tub based on the
measured value, and determining whether to initialize the
dewatering process at the detection section based on the determined
predicted value of the maximum vibration displacement and a
predetermined reference value.
[0043] According to an embodiment disclosed herein, the vibration
sensor may measure a plurality of vibration displacement values for
a plurality of vibrations occurring along a plurality of different
axes with respect to the tub.
[0044] According to an embodiment disclosed herein, the measuring
may be configured to calculate information of a plurality of phase
differences between the plurality of vibrations.
[0045] According to an embodiment disclosed herein, the information
of the plurality of phase differences may include information
regarding phase differences between any one of the plurality of
vibrations and the remaining vibrations.
[0046] According to an embodiment disclosed herein, the determining
may be configured to output the predicted value of the maximum
vibration displacement as an output value by inputting at least one
of the plurality of vibration displacement values, the information
of the plurality of phase differences, and a rotational speed
variation value as an input value of a pre-trained Artificial
Neural Network (ANN).
[0047] According to an embodiment disclosed herein, the predicted
value of the maximum vibration displacement may include a plurality
of predicted values of a maximum vibration expected to be generated
in each of a plurality of different axes of different axes.
[0048] According to an embodiment disclosed herein, rotating the
drum faster than a specific rotational speed at the detection
section may be further included, when all of the plurality of
predicted values of the maximum vibration displacement are equal to
or less than the predetermined reference value.
[0049] According to an embodiment disclosed herein, the determining
whether to initialize the dewatering process may be configured such
that the dewatering process is initialized by stopping rotation of
the drum at the detection section when at least one of the
plurality of predicted values of the maximum vibration displacement
exceeds the predetermined reference value.
[0050] According to an embodiment disclosed herein, the
predetermined reference value may be set according to each of a
plurality of different axes.
[0051] According to an embodiment disclosed herein, the specific
rotational speed may be faster than a speed of the drum rotating
while the laundry is attached to a wall surface of the drum, and
slower than a maximum rotational speed of the dewatering
process.
[0052] The embodiments of the present disclosure may provide at
least one or more of the following benefits:
[0053] One, the maximum vibration displacement of a tub expected to
be generated during a dewatering process is predicted at a
detection section, thereby determining whether to initialize the
dewatering process or continue the dewatering process at the
beginning (or at an early stage) of dewatering.
[0054] Two, unbalance (UB) that causes excessive vibration to occur
may be detected at the beginning of the dewatering process.
Accordingly, the dewatering process may be initialized early,
thereby reducing time required for dewatering.
[0055] Three, if a predicted value of the maximum vibration
displacement calculated through an ANN exceeds a predetermined
reference value, it may be determined to initialize (stop or
terminate) the dewatering process without continuing it further,
thereby preventing excessive vibration from occurring, and reducing
time taken to enter the dewatering process.
[0056] It is understood that the effects and benefits of the
present disclosure are not limited to those described above, and
other effects not mentioned may be clearly understood by those
skilled in the art from the description of the appended claims.
BRIEF DESCRIPTION OF THE DRAWINGS
[0057] The accompanying drawings constitute a part of this
specification and illustrate an embodiment of the present
disclosure and together with the specification, explain the present
disclosure.
[0058] FIG. 1 is a lateral cross-sectional view of a washing
machine according to an embodiment of the present disclosure.
[0059] FIG. 2 is a block diagram illustrating a control
relationship between main components of the exemplary washing
machine of FIG. 1.
[0060] FIG. 3 is a view illustrating an exemplary process of a
dewatering cycle according to an embodiment of the present
disclosure.
[0061] FIGS. 4(a) and (b) are conceptual views illustrating
rotational speed fluctuations and 3D UB according to an embodiment
of the present disclosure.
[0062] FIG. 5 is a flowchart illustrating a representative control
method according to an embodiment of the present disclosure.
[0063] FIG. 6 is a conceptual view illustrating the control method
in FIG. 5.
[0064] FIG. 7 is a conceptual view illustrating the control method
in FIG. 5.
[0065] FIG. 8 is a conceptual view illustrating the control method
in FIG. 5.
[0066] FIG. 9 is a conceptual view illustrating the control method
in FIG. 5
[0067] FIG. 10 includes data resulting from experiments employing a
control method according to an embodiment of the present
disclosure.
[0068] FIG. 11 includes data resulting from experiments employing a
control method according to an embodiment of the present
disclosure.
DETAILED DESCRIPTION OF THE DISCLOSURE
[0069] Hereinafter, the embodiments disclosed herein will be
described in detail with reference to the accompanying drawings,
and the same or similar elements are designated with the same
numeral references regardless of the numerals in the drawings and
their redundant description will be omitted. In general, a suffix
such as "module" and "unit" may be used to refer to elements or
components. Use of such a suffix herein is merely intended to
facilitate description of the specification, and the suffix itself
is not intended to give any special meaning or function. In
describing the present disclosure, if a detailed explanation for a
related known technology or construction is considered to
unnecessarily divert the gist of the present disclosure, such
explanation has been omitted but would be understood by those
skilled in the art. Also, it should be understood that the
accompanying drawings are merely illustrated to easily explain the
concept of the disclosure, and therefore, they should not be
construed to limit the technological concept disclosed herein by
the accompanying drawings, and the concept of the present
disclosure should be construed as being extended to all
modifications, equivalents, and substitutes included in the concept
and technological scope of the disclosure.
[0070] Though the terms including an ordinal number such as first,
second, etc. may be used herein to describe various elements, the
elements should not be limited by those terms. The terms are used
merely for the purpose to distinguish an element from another
element.
[0071] If a component is described as being "connected", "coupled"
or "connected" to another component, it should be understood that
the component may be directly connected or connected to that other
component, but having other components there between. Thus, it will
be understood that when an element is referred to as being
"connected with" another element, the element can be directly
connected with the other element or intervening elements may also
be present. On the contrary, in case where an element is "directly
connected" or "directly linked" to another element, it should be
understood that any other element is not existed therebetween.
[0072] A singular representation may include a plural
representation as far as it represents a definitely different
meaning from the context.
[0073] Terms "include" or "has" used herein should be understood
that they are intended to indicate the existence of a feature, a
number, a step, a constituent element, a component or a combination
thereof disclosed in the specification, and it may also be
understood that the existence or additional possibility of one or
more other features, numbers, steps, constituent elements,
components or combinations thereof are not excluded in advance.
[0074] Unless otherwise defined, all terms including technical and
scientific terms used herein have the same meaning as commonly
understood by one of ordinary skill in the art to which this
inventive concept belongs. It will be further understood that
terms, such as those defined in commonly used dictionaries, should
be interpreted as having a meaning that is consistent with their
meaning in the context of the relevant art and will not be
interpreted in an idealized or overly formal sense unless expressly
so defined herein. FIG. 1 is a lateral cross-sectional view of a
washing machine according to an embodiment of the present
disclosure. FIG. 2 is a block diagram illustrating a control
relationship between main components of the washing machine of FIG.
1.
[0075] Referring to FIG. 1, a washing machine may include a casing
1 forming an outer appearance of the washing machine, a water
storage tank (or tub) 3 disposed in the casing 1 and configured to
hold wash water therein, a washing tub 4 (or drum) rotatably
disposed inside the water storage tank 3 into which laundry may be
disposed, and a motor 9 configured to drive and rotate the washing
tub 4.
[0076] The washing tub 4 may be provided with a front cover 41
having an opening for insertion and removal of laundry, a
cylindrical drum 42 substantially horizontally disposed so that a
front end thereof is coupled to the front cover 41, and a rear
cover 43 is coupled to a rear end of the drum 42. A rotating shaft
of the motor 9 may be connected to the rear cover 43 by passing
through a rear wall of the water storage tank 3. A plurality of
through holes may be formed in the drum 42 so that water is
exchanged between the washing tub 4 and the water storage tank
3.
[0077] A lifter 20 may be provided on an inner circumferential
surface of the drum 42. The lifter 20 may protrude from the inner
circumferential surface of the drum 42 and may extend along a
lengthwise direction (a forward-backward direction) of the drum 42.
A plurality of the lifters 20 may be disposed to be spaced apart
from each other in a circumferential direction. Laundry may be
lifted up by the lifter 20 when the washing tub 4 is rotated.
[0078] It is not limited to this, but a preferable height of the
lifter 20 protruding from the drum 42 is 30 mm or less (or 6.0% of
a drum diameter), and more preferably 10 to 20 mm. Particularly,
when the height of the lifter 20 is 20 mm or less, even if the
washing tub 4 is continuously rotated in one direction at
approximately 80 rpm, laundry may be moved without being attached
to the washing tub 4. For example, when the washing tub 4 rotates
in one direction more than once, the laundry located at the
lowermost position in the washing tub 4 may be lifted up to a
predetermined height by the rotation of the washing tub 4 and then
dropped while being separated from the washing tub 4.
[0079] The washing tub 4 may be rotated centered on a horizontal
axis. Here, the term "horizontal" does not mean geometric
horizontal in the strict sense, but it is closer to horizontal than
vertical even when it is inclined at a predetermined angle with
respect to the horizontal axis as shown in FIG. 1. Thus, it is
understood that the washing tub rotates with respect to the
horizontal axis.
[0080] A laundry inlet may be formed at a front surface of the
casing 1, and a door 2 for opening and closing the laundry inlet
may be rotatably provided at the casing 1. A water inlet valve 5, a
water inlet pipe 6, and a water inlet hose 8 may be installed in
the casing 1. When the water inlet valve 5 is opened for supplying
water, wash water having passed through the water inlet pipe 6 may
be mixed with a detergent in a dispenser 7, and then introduced
into the water storage tank 3 through the water inlet hose 8.
[0081] An input port of a pump 11 may be connected to the water
storage tank 3 through a drain hose 10, and an outlet port of the
pump 11 may be connected to a drain pipe 12. The water discharged
from the water storage tank 3 through the drain hose 10 flows along
the drain pipe 12, and is then discharged to the outside of the
washing machine.
[0082] Referring to FIG. 2, the washing machine according to one
embodiment of the present disclosure may include a controller 60
configured to control an entire operation of the washing machine, a
motor drive unit 71 controlled by the controller 60, an output unit
72, a communication unit 73, a speed sensing unit 74, a current
sensing unit 75, a vibration sensing unit 76, and a memory 78. For
example, the controller 60 may be a microprocessor, an integrated
circuit, an electrical circuit, and the like.
[0083] The controller 60 may control a series of washing processes
of washing, rinsing, dewatering, and drying. The controller 60 may
perform a washing cycle, a rinsing cycle, a dewatering cycle, and a
drying cycle according to a preset algorithm. The controller 60 may
also control the motor drive unit 71 according to the
algorithm.
[0084] The motor drive unit 71 may control driving of the motor 9
in response to a control signal applied by the controller 60. The
control signal may be a signal for controlling a target speed of
the motor 9, an acceleration tilt (or acceleration), a driving
time, and the like.
[0085] The motor drive unit 71 powers the motor 9, which may
include an inverter (not shown) and an inverter controller (not
shown). In addition, the motor drive unit 71 may include a
converter or the like used for supplying direct current (DC) power
to the inverter.
[0086] For example, when the inverter controller (not shown)
outputs a switching control signal of a Pulse Width Modulation
(PWM) based method to the inverter (not shown), then the inverter
(not shown) performs high switching so as to supply alternating
current (AC) power of a predetermined frequency to the motor 9.
[0087] In this disclosure, for example, controlling the motor 9 in
a specific manner by the controller 60 may mean that the controller
60 applies a control signal to the motor drive unit 71 so that the
motor drive unit 71 controls the motor 9 in the specific manner
based on the control signal. Here, the specific manner may include
various embodiments described herein.
[0088] The speed sensing unit 74 (or speed sensor) may detect a
rotational speed of the washing tub 4. The speed sensing unit 74
may detect a rotational speed of a rotor of the motor 9. When a
planetary gear train that rotates the washing tub 4 by changing a
revolution ratio of the motor 9 is provided, the rotational speed
of the washing tub 4 may be a value converted to the rotational
speed of the rotor sensed by the speed sensing unit 74 in
consideration of a deceleration or acceleration ratio of the
planetary gear train.
[0089] The controller 60 may control the motor drive unit 71 such
that the motor 9 follows a preset target speed by using feedback on
a rotational speed of the washing tub 4 received from the speed
sensing unit 74. In other words, the controller 60 may control the
motor 9 such that the rotational speed of the washing tub 4 reaches
the target speed.
[0090] The current sensing unit 75 (or current sensor) may detect
an electric current applied to the motor 9 (or an output current
flowing in the motor 9) to transmit the sensed current to the
controller 60. The controller 60 may detect a load (or amount) of
laundry and a kind of fabric (or laundry item) using the received
current.
[0091] Here, values of the electric current include values obtained
during a process in which the washing tub 4 is accelerated toward
the target speed (or a process in which the motor 9 is accelerated
toward the preset target speed).
[0092] When rotation of the motor 9 is controlled by vector control
based on a torque current and a magnetic flux current, the current
may be a torque axis (q-axis) component flowing in a motor circuit,
namely, a torque current (Iq).
[0093] The vibration sensing unit 76 may detect vibration in the
water storage tank 3 (or washing machine) generated by rotation of
the washing tub 4 in which laundry is accommodated.
[0094] The washing machine according to an embodiment of the
present disclosure may include a vibration sensor (or a vibration
measurement sensor) 77. The vibration sensor 77 may be provided at
one location of the washing machine, e.g., attached to the water
storage tank 3. The vibration sensor 77 may be included in the
vibration sensing unit 76.
[0095] The vibration sensing unit 76 may receive a vibration value
(or a vibration displacement value) measured by the vibration
sensor 77, and transmit the vibration value to the controller 60.
The vibration sensing unit 76 may calculate a vibration value (or
vibration displacement value) of the water storage tank 3 (or
washing machine) using a vibration signal measured by the vibration
sensor 77. The vibration sensing unit 76 may be implemented as a
vibration sensor. On the other hand, the vibration sensing unit 76
may be mounted to a specific location to be able to detect abnormal
vibration of the washing machine, or may be implemented as an
acceleration sensor mounted to be able to simultaneously detect a
plurality of positions of the abnormal vibration.
[0096] The speed sensing unit 74, the current sensing unit 75, and
the vibration sensing unit 76 provided in the washing machine
according to one embodiment of the present disclosure may also be
referred to as a "sensing unit", and be understood as a concept
included in the sensing unit.
[0097] The sensing unit may calculate a rotational speed value (or
speed value) of the washing tub 4 measured by the speed sensing
unit 74, an electric current value applied to the motor 9, which is
measured by the current sensing unit 75, and a vibration value of
the water storage tank 3 measured by the vibration sensing unit
76.
[0098] The washing machine according to an embodiment of the
present disclosure may include a UB sensing unit (not shown). The
UB sensing unit may sense an amount of eccentricity (amount of
shaking) of the washing tub 4, that is, unbalance (UB) of the
washing tub 4. The UB sensing unit may calculate a UB value that
numerically represents shaking of the washing tub 4.
[0099] The controller 60 may calculate Rotational Revolution per
Minute (RPM) of the washing tub 4 as the UB value. For example, the
controller 60 may calculate a displacement value between the
maximum speed and the minimum speed as a rotational speed variation
(or shaking) value, based on a waveform value of a rotational speed
of the washing tank 4 measured by the speed sensing unit 74.
[0100] The UB value may be the calculated rotational speed
variation value itself, or may be a specific value output by using
the calculated rotational speed variation value.
[0101] The controller 60 may measure unbalance (UB) of the washing
tub 4 generated when the washing tub 4 accommodating laundry
therein rotates. Here, unbalance of the washing tub 4 may mean
shaking of the washing tub 4 or a shaking value (or a degree of
shaking) of the washing tub 4. In addition, the unbalance of the
washing tank 4 may mean there is an uneven distribution of weight
of the laundry in the washing tank 4.
[0102] The controller 60 may measure (calculate) a shaking value
(or degree of shaking) of the washing tub 4 (or drum). The shaking
value of the washing tub 4 may be referred to as a UB value, an
amount of UB, an unbalance value, an amount of unbalance, or an
amount of eccentricity.
[0103] In this disclosure, unbalance (UB) may mean the amount of
eccentricity of the washing tub 4, that is, unbalance of the
washing tub 4 or amount of shaking of the washing tub 4.
[0104] The UB value that represents an intensity (or a degree) of
shaking of the washing tub 4 may be output (calculated) based on an
amount of rotational speed variations of the washing tub 4 (or
motor 9), or an amount of acceleration variations of the washing
tub 4 (or the motor 9).
[0105] For example, the controller 60 may calculate the UB value by
receiving the rotational speed of the washing tub 4 (or motor 9)
measured by the speed sensing unit 74 and using the amount of
variations in the received rotational speed value. Here, the amount
of rotational speed variations may mean, for example, a difference
in rotational speeds measured at predetermined time intervals, a
difference in rotational speeds measured at each time when the
washing tub 4 is rotated by a predetermined angle, or a difference
between the maximum rotational speed and the minimum rotational
speed. That is, the UB value described herein may mean a rotational
speed variation value (or RPM fluctuations).
[0106] For example, the controller 60 may measure the rotational
speed of the washing tub 4, measured by the speed sensing unit 74,
at each predetermined angle to calculate acceleration through a
difference in the measured rotational speeds. Thereafter, the
controller 60 (or UB sensing unit (not shown)) may calculate the UB
value by using a value obtained by subtracting the minimum
acceleration from the maximum acceleration in the measured
rotational speed values.
[0107] Meanwhile, in the figures, the speed sensing unit 74, the
current sensing unit 75, the vibration sensing unit 76, and the UB
sensing unit (not shown) are provided separate from the controller
60, but it is understood that the invention is not limited
thereto.
[0108] At least one of the speed sensing unit 74, the current
sensing unit 75, the vibration sensing unit 76, and the UB sensing
unit may be provided in the controller 60. In this case, functions,
operation, and control methods performed by the speed sensing unit
74, the current sensing unit 75, and the vibration sensing unit 76,
and the UB sensing unit may be performed by the controller 60.
[0109] When the vibration sensing unit 76 is included in the
controller 60 or is performed under the control of controller 60,
it may be understood that the vibration sensor 77 is not included
in the vibration sensing unit 76, but is separately provided at one
point of the washing machine. Here, the one point of the washing
machine may be a point of an outer surface of the water storage
tank 3.
[0110] The output unit 72 may output various information related to
a washing machine. For example, the output unit 72 may output an
operating state of the washing machine. The output unit 72 may be
an image output device that outputs a visual display such as an LCD
or LED, or an acoustic output device that outputs sound such as a
buzzer. The output unit 72, controlled by the controller 60, may
output information of the amount of laundry or the kind of fabric
(laundry item).
[0111] A programmed ANN, an electric current pattern according to
the amount of laundry and/or the kind of fabric, a database (DB)
constructed by machine learning based on the electric current
pattern, a machine learning algorithm, current values detected by
the current sensing unit 75, average values of the detected current
values, values obtained by processing the average values according
to a parsing rule, and data transmitted and received through the
communication unit 73, and the like may be saved in the memory
78.
[0112] In addition, data such as control data for controlling the
entire operation of the washing machine, data of washing settings
input by a user, data of wash time calculated according to the
washing settings, data of wash courses, data for determining a
washing machine error, and the like may be saved in the memory
78.
[0113] The communication unit 73 may communicate with a server
connected wirelessly to a network. The communication unit 73 may
include at least one communication module such as an Internet
module, a mobile communication module, etc. The communication unit
73 may receive various types of data such as learning data and
algorithm updates from the server.
[0114] The controller 60 may update the memory 78 by processing
various types of data received from the communication unit 73. For
example, in case data input through the communication unit 73 is
related to an update of an operation program prestored in the
memory 78, the controller 60 may update the memory 78 using update
data. When the input data is about a new operation program, the
controller 60 may additionally store the new operation program in
the memory 78.
[0115] For purposes of this disclosure, it is understood that
"machine learning" refers to a computer learning from data and
solving a problem without being explicitly instructed logic by a
person.
[0116] Deep learning, an artificial intelligence (AI) technology,
is based on an ANN for constructing AI so that a computer thinks
and learns like people without having to teach it. The ANN may be
implemented in the form of software or hardware such as a chip.
[0117] For example, the controller 60, based on the machine
learning, may figure out properties of laundry (fabric)
(hereinafter, referred to as "properties of fabric") introduced
into the washing tub 4 by processing electric current values sensed
by the current sensing unit 75. These properties of fabric may
include the amount of the laundry, and the kind (or type) of fabric
or material (e.g., cotton, polyester, etc.).
[0118] In addition, the controller 60 may determine (predict,
estimate, calculate) various information related to unbalance of
the washing tub 4 according to the present disclosure using the ANN
learned through machine learning. For example, the controller 60
may calculate a predicted value of the maximum vibration
displacement expected to be generated in a dewatering process.
[0119] When the laundry is concentrated at one side of the washing
tub 4 or laundry is severely tangled, unbalance may occur (i.e.,
unbalance becomes severe), causing the washing tub 4 to shake or
vibrate while rotating.
[0120] As shaking of the washing tub 4 increases and/or becomes
severe (e.g., as the UB value of the washing tub 4 increases), an
increased current load is applied to the motor 9 for rotating the
washing tub 4 at high speed, thereby consuming more energy and
causing more noise.
[0121] In contrast, when laundry is substantially evenly
distributed in the washing tub 4 or laundry is not tangled or
slightly tangled, the likelihood of unbalance is reduced.
Accordingly, even if the washing tub 4 is rotated at high speed,
shaking (vibration value) of the washing tub 4 is reduced, and the
UB value becomes smaller.
[0122] Hereinafter, a method for minimizing unbalance (UB) caused
by laundry will be described in detail.
[0123] FIG. 3 is a view illustrating a process of a dewatering
cycle according to an embodiment of the invention. FIGS. 4(a) and
(b) are conceptual views illustrating rotational speed fluctuations
and 3D UB according to an embodiment of the invention.
[0124] The washing machine according to this embodiment may perform
a dewatering cycle (or stroke) by using a dewatering driving
algorithm, so as to minimize UB caused by laundry (or fabric).
[0125] Hereinafter, the water storage tank 3 described above will
be referred to as tub 3, and the washing tub 4 described above will
be referred to as drum 4.
[0126] In terms of vibrations of a drive unit (a tub that includes
a drum) of the washing machine, the maximum vibration displacement
amplitude of the drive unit and an occurring point tend to vary
according to a load of laundry (an amount of fabrics). Accordingly,
the washing machine detects a load of laundry (or an amount of
laundry) when the laundry is turned over at a low rotational speed
(RPM) (e.g., less than 50 RPM).
[0127] The load of laundry may be detected by monitoring an
electric current in the motor 9. The controller 60 of the washing
machine may accurately predict the load of laundry via deep
learning. Thereafter, a laundry distribution process (or laundry
balancing process) may be performed to evenly load or distribute
laundry in the drum 4 while rotating and decelerating (about 50 RPM
or less) the drum 4 (2 of FIG. 3). The controller 60 may monitor a
degree (level) of laundry distribution using an electric current in
real time. In addition, when the controller 60 detects a
predetermined amount of electric current, it may move onto a UB
detection process for detecting unbalance (UB) caused by
laundry.
[0128] The unbalance (UB) detection may be performed in a state
when the centrifugal force is applied to an extent that keeps
laundry fixed while the laundry is compressed against an inner wall
of the drum 4.
[0129] Although slightly different depending on a diameter of the
drum, or the like, unbalance (UB) is usually generated when laundry
is compressed against the inner wall of the drum 4 while the drum 4
is rotated at 80 to 90 RPM or more.
[0130] Accordingly, the UB detection may performed at 80 to 90 RPM
or more. For example, it may be performed at a specific rotational
speed (108 RPM) faster than the rotational speed of 80 to 90
RPM.
[0131] As such, a section in which unbalance (UB) is detected while
rotation of the drum 4 is maintained at the specific rotational
speed (108 RPM) will be referred to as "detection section".
[0132] For the same reason, the laundry distribution process for
mixing and evenly distributing laundry (items) may be performed at
80 RPM or less at which the laundry does not compress against the
drum 4.
[0133] Meanwhile, in a resonance section of 150 to 600 RPM where
the maximum vibration displacement of the drive unit is generated
during dewatering, vibration displacement may be rapidly changed
due to multi-directionality and nonlinearity of vibration.
[0134] Thus, the UB detection should be performed between 80 to 150
RPM at which unbalance (UB) is fixed but vibration displacement
variation is not large.
[0135] A UB detection technique will be described in detail with
reference to FIGS. 4(a) and (b).
[0136] Through a series of algorithms in a UB detection step
(detection section), when a value of vibration displacement due to
unbalance (UB) is expected to exceed a reference value if
accelerated to a higher RPM, the controller 60 may control a
rotational speed of the drum 4 to return to 0 RPM to stop, so as to
repeat a series of steps after detecting the load of laundry (1
(Dewatering process is stopped when detected UB exceeds reference
value) of FIG. 3).
[0137] At this time, the reference value of the vibration
displacement value may be determined by taking various or complex
matters such as an occurrence of collision between the drive unit
and the cabinet, noise, and a rigidity limit of the drive unit into
consideration.
[0138] When the value of vibration displacement caused by unbalance
(UB) is not expected to exceed the reference value, the controller
60 may accelerate the drum 4 to a higher RPM, so as to increase a
dewatering rate (or level).
[0139] If vibration is greatly generated during acceleration unlike
the predicted unbalance (UB), the controller 60 terminates or stops
rotation of the drum 4 before excessive vibration exceeding a
reference vibration value occurs, so as to restart the dewatering
stroke from a step after detecting the load of laundry (3 of FIG.
3).
[0140] Stopping the rotation of the drum 4 or returning the
rotational speed of the drum 4 to 0 RPM and repeating a series of
processes (or steps) after detecting the load of laundry may be
referred to as "initializing the dewatering process" or
"terminating the dewatering process".
[0141] Here, in case a sensor for measuring vibration is provided,
the controller 60 may terminate the rotation of the drum 4 when a
measured vibration displacement value exceeds a predetermined
reference value. In case a sensor is not provided, the controller
60 may continuously monitor an electric current value used for
driving the motor to estimate a vibration displacement value, and
terminate the rotation of the drum 4 when the predicted vibration
displacement value exceeds the predetermined reference value.
[0142] For example, when a large amount of different types of
fabrics are mixed together, changes in unbalance (UB) due to the
different types of fabrics (or laundry items) may occur as the
degree of drainage generally varies depending on the type of
fabric.
[0143] To reflect changes in unbalance (UB) at high RPM,
acceleration and deceleration are repeated several times to
repeatedly detect unbalance (UB) in a drained state.
[0144] When UB detection at 108 RPM is performed repeatedly while
accelerating and decelerating RPM to drain water, 1) passing all
the UB detection performed several times, 2) entering main
dewatering when an actual vibration displacement value does not
exceed the predetermined reference value after increasing RPM, and
carrying out dewatering at high RPM. As for cases other than 4
(dewatering process is continued as vibration reference is
satisfied, when accelerating) of FIG. 3, the dewatering process (or
rotation of the drum) is stopped to evenly distribute laundry
again.
[0145] Ideally, vibration and noise are reduced to a minimum amount
when unbalance (UB) is removed through perfect or substantially
perfect balancing in the dewatering step. However, if UB detection
is excessively performed for this purpose, time required for
dewatering (dewatering entry time) will be extended, causing a
prolonged time of an entire wash cycle. Therefore, an algorithm is
constructed by considering that there is a trade-off between
vibration/noise and a dewatering entry time.
[0146] A method for UB detection will be described with reference
to FIGS. 4(a)-(b).
[0147] In the dewatering step, unbalance (UB) detection may be
performed through changes in a rotational speed generated when a
constant amount of electric current is input to the motor to
maintain the specific rotational speed (108 RPM).
[0148] When laundry is positioned at an upper part or portion of
the drum 4 while the drum 4 is rotating ({circle around (1)} of
FIG. 4(a)), a force generated by a drop of the laundry, as the drum
4 rotates, acts to accelerate RPM of the drum 4 (e.g., causing RPM
to increase).
[0149] In contrast, when laundry is positioned at a lower part or
portion of the drum 4 ({circle around (2)} of FIG. 4(a)), gravity
applied to the laundry acts in a direction that impedes or suppress
rotation of the drum 4, thereby decelerating RPM of the drum 4
(e.g., causing RPM to decrease).
[0150] In addition, a range of RPM fluctuation may vary depending
on a size or amount of laundry (or a level (or degree) of an
unbalanced load of laundry). As such, the range of RPM fluctuations
may mean a rotational speed variation (or shaking) value or an RPM
variation (or shaking) value, and may also mean a UB value (or a
level of UB).
[0151] In general, the level of unbalance (UB) determines a
magnitude of the maximum vibration displacement that occurs in a
transient section (or region). By considering a correlation between
the range of RPM fluctuations and the magnitude of the maximum
vibration displacement in the transient section, the controller 60
determines whether to stop rotation of the drum 4 or to enter a
main dewatering process.
[0152] In addition to the RPM fluctuations, the controller 60 may
calculate a vibration displacement value using the vibration sensor
77 attached to the tub 3 for directly measuring vibration (or
vibration displacement value), and compare the vibration
displacement (amplitude) at the detection section (108 RPM) with a
specific reference value to determine whether the rotation of the
drum 4 is terminated. Here, the specific reference value may be
determined using a correlation between a vibration magnitude
(level) at the detection section (108 RPM) and the maximum
vibration displacement in the transient section.
[0153] Meanwhile, in the case of a large load of laundry, unbalance
(UB) may not be seen as one, as illustrated in FIG. 4(a), the UB is
distributed in three dimensions by a depth direction of the drum 4,
an angle, etc.
[0154] As illustrated in FIG. 4(b), in case unbalance (UB) with a
specific angle is generated in the front and rear of the drum 4
(diagonal UB, or 3D UB), RPM fluctuations caused by a fabric (or
laundry item) m_f, m_r placed on the front and rear of the drum 4,
respectively, are offset with each other, when the rotational speed
variation value (the range of fluctuations) is observed through the
method described in FIG. 4(a), thereby generating relatively small
RPM fluctuations.
[0155] Even when using the vibration sensor, a high-dimensional
mode is not generated in the detection section (detection RPM)
where the drum 4 is rotated at the specific rotational speed (108
RPM). Accordingly, vibration is linearly increased in the case of a
small load of laundry. As for the diagonal UB (3D UB), however, the
RPM fluctuations are offset, resulted in a small amount of
vibration. Thus, it is difficult to predict vibration expected to
be generated at RPM higher than the specific rotational speed (108
RPM) only with vibration displacement measured in the detection
section where the drum 4 is rotated at the specific rotational
speed (108 RPM).
[0156] Meanwhile, in the case of 150 to 600 RPM (transient section)
at which the maximum vibration displacement occurs due to resonance
of the drum 4, the high-dimensional vibration mode is observed,
which is not observable at low RPM.
[0157] Due to the complex action of the high-dimensional vibration
mode, nonlinear vibration occurs. Accordingly, it is difficult to
accurately predict an amount of vibration (vibration displacement
value) in the transient section using the conventional method in
which complex UB (diagonal UB, 3D UB) of a large load is not
properly detected.
[0158] If a determination on whether to stop (or terminate) the
dewatering process (or rotation of the drum) based on UB detection
is made incorrectly, a problem occurs in terms of both vibration
and a dewatering entry time.
[0159] When the main dewatering process is proceeded due to
incorrect detection even if unbalance (UB) is severe, it causes
excessive vibration in the transient section, and rotation of the
drum 4 to stop. And the dewatering stroke is restarted from the
beginning, leading to a delay in the dewatering entry time compared
when the dewatering process is stopped at the time of the UB
detection.
[0160] On the contrary, when the dewatering process is stopped even
if unbalance (UB) is small and no excessive vibration occurs, it
causes a delay in the dewatering entry time compared to an
opportunity to enter the dewatering process.
[0161] In order to reduce time required for dewatering, the washing
machine according to the present disclosure may calculate (or
determine), at the start of the dewatering process, a predicted
value of the maximum vibration displacement that might be generated
during the dewatering process, and determine whether to initialize
the dewatering process, or enter the main dewatering process based
on the calculated predicted value of the maximum vibration
displacement.
[0162] Hereinafter, an optimized method for controlling a washing
machine will be described according to an embodiment of the
invention. In the method, the maximum vibration displacement
expected to be generated in the transient section (predicted
maximum vibration displacement that might be generated during the
dewatering process) is accurately predicted at the UB section (at
the beginning of the dewatering process) where unbalance (UB) is
detected at the specific rotational speed, so as to initialize the
dewatering process to evenly distribute laundry before excessive
vibration occurs or reduce time required for dewatering by entering
the main dewatering process quickly if no excessive vibration
occurs.
[0163] FIG. 5 is a flowchart illustrating a representative control
method according to an embodiment of the invention. FIGS. 6, 7, 8,
and 9 are exemplary conceptual views illustrating the control
method in FIG. 5.
[0164] First, in the detection section (section in which a
rotational speed of the drum 4 is maintained at the specific
rotational speed of 108 RPM), the washing machine may predict the
maximum vibration displacement, which is usually generated in the
transient section (150 to 600 RPM), to determine whether to
initialize or continue the dewatering process at the beginning of
the dewatering process. That is, the maximum vibration displacement
of the tub 3 generated in the transient section may mean the
maximum vibration displacement expected to be generated in the
entire dewatering process.
[0165] In other words, the washing machine may determine on whether
or not excessive vibration will be generated in the transient
section (150 to 600 RPM) based on distribution of a load of laundry
(UB) in the drum 4 at the beginning of the dewatering process
(detection section).
[0166] For example, if the load of laundry in the drum 4 is
unevenly distributed or unbalanced, a rotational speed of the drum
4 becomes faster, thereby increasing a possibility of excessive
vibration occurring in the transient section.
[0167] To solve this problem, the washing machine according to this
embodiment may include the vibration sensor 77 provided at the tub
3 to predict a maximum vibration displacement value of the tub 3.
Here, the vibration sensor 77 may be a 6-axis vibration sensor.
[0168] To predict the maximum vibration displacement value of the
tub 3, a vibration displacement value and a phase measured at the
detection section (108 RPM) by the 6-axis vibration sensor 77
together with an RPM variation value are input into an ANN learned
through 3D unbalance (UB) deep learning as an input value, so as to
obtain a predicted value of the maximum vibration displacement of
the tub 3 as an output value.
[0169] The controller 60 may input a plurality of vibration
displacement values, and information of a plurality of phase
differences calculated based on the plurality of vibration
displacement values measured by the vibration sensor 77, and a
rotational speed variation value into a pre-trained or pre-learned
ANN as input values, so as to output a predicted value of the
maximum vibration displacement expected to be generated in the
entire dewatering process as a result value.
[0170] Thereafter, the controller 60 may compare the predicted
value of the maximum vibration displacement with a predetermined
reference value to determine whether to initialize (terminate) the
dewatering process or to continue the dewatering process at the
beginning of the dewatering process.
[0171] For example, when the predicted value of the maximum
vibration displacement exceeds the predetermined reference value,
the controller 60 may stop the dewatering process, and initialize
(terminate) the dewatering process to prevent excessive vibration,
thereby decreasing time required to enter the main dewatering
process (process in which dewatering is performed at 108 RPM).
[0172] Hereinafter, an exemplary process of calculating a predicted
value of the maximum vibration displacement will be described with
reference to accompanying drawings.
[0173] First, a washing machine according to this embodiment may
include a tub 3, and a drum 4 accommodating a vibration sensor 77
provided at the tub 3, and a fabric (laundry) disposed therein, and
provided to be rotatable in the tub 3.
[0174] In addition, the washing machine may include a motor 9 for
rotating the drum 4, and a controller 60 configured to control the
motor 9 by using a vibration value (hereinafter referred to as
"vibration displacement value") measured by the vibration sensor
77.
[0175] Referring to FIG. 5, the controller 60 may measure a value
regarding multi-axis vibration generated in the tub 3 that includes
the drum 4 at a detection section where the drum 4 is rotated at a
specific rotational speed (e.g., 108 RPM) during a dewatering
process (S510).
[0176] The specific rotational speed may be greater (faster) than a
speed at which the drum 4 is rotated while laundry is attached to a
wall surface of the drum 4, and less (slower) than a maximum
rotational speed of the dewatering process.
[0177] That is, the specific rotational speed may be faster than a
minimum speed at which the drum 4 starts to rotate while the
laundry is compressed against or adhered to the wall surface of the
drum 4 (for example, it may vary depending on a diameter of the
drum, but generally between 80 and 90 RPM), and may be slower than
a speed, for example, 108 RPM, which is slower than the maximum
rotational speed of the dewatering process (e.g., 600 RPM) or a
transient section (resonance section) (e.g., 150 to 600 RPM).
[0178] As described above, the vibration sensor 77 may be a 6-axis
vibration sensor.
[0179] The "multi-axis" may mean a plurality of different axes that
can be measured by the vibration sensor (e.g., 6-axis, in case the
vibration sensor is capable of sensing vibration in 6 axes).
[0180] A value related to the multi-axis vibration may include a
plurality of vibration displacement values for a plurality of
vibrations measured based on a plurality of different axes and
information of a plurality of phase differences between the
plurality of vibrations.
[0181] That is, the value related to the multi-axis vibration may
mean a displacement and a phase (or phase difference) value of the
multi-axis vibration (the plurality of vibrations).
[0182] The vibration sensor 77 may measure a plurality of vibration
displacement values for a plurality of vibrations occurring along a
plurality of different axes (e.g., 6 axes) with respect to the tub
3.
[0183] Here, the plurality of different axes (6 axes) may mean 6
different axes, and may mean axes having a plurality of different
directions at a plurality of different points (or locations) of the
tub 3. In other words, the plurality of different axes may mean
axes, each having a different direction at a different point of the
tub 3.
[0184] Referring to FIG. 6, the plurality of different points of
the tub 3 may mean a front point F and a rear point R of the tub 3.
The plurality of different directions may include a
forward-and-backward direction x, a left-and-right direction y
perpendicular to the forward-and-backward direction, and an
up-and-down direction z perpendicular to the forward-and-backward
direction and the left-and-right direction, respectively.
[0185] The plurality of different axes (6 axes) may be formed by a
combination of a plurality of different directions at each of the
plurality of different points. For example, the 6 axes may include
a front forward-backward axis Fx, a front left-right axis Fy, a
front up-down axis Fz, a rear forward-backward axis Rx, a rear
left-right axis Ry, and a rear up-down axis Rz.
[0186] The vibration sensor 77 may measure a plurality of vibration
displacement values for a plurality of vibrations occurring along
the plurality of different axes Fx, Fy, Fz, Rx, Ry, and Rz with
respect to the tub 3 (or in the tub 3). That is, the vibration
sensor 77 may measure a plurality of displacement values of
vibrations occurring in the plurality of different directions (x,
y, z) at the different points (F, R) of the tub 3.
[0187] The vibration sensor 77 may be disposed at one location of
the tub 3 to classify vibrations generated in the tub 3 into a
plurality of vibrations based on the plurality of different axes,
and a plurality of vibration displacement values for the plurality
of vibrations may be measured.
[0188] The plurality of vibration displacement values may include a
front forward-backward vibration displacement value (Fx vibration
displacement value), a front left-right axis vibration displacement
value (Fy vibration displacement value), a front up-down vibration
displacement value (Fz vibration displacement value), a rear
forward-backward vibration displacement value (Rx vibration
displacement value), a rear left-right vibration displacement value
(Ry vibration displacement value), and a rear up-down vibration
displacement value (Rz vibration displacement value).
[0189] In addition, the controller 60 may calculate information of
a plurality of phase differences between the plurality of
vibrations occurring along the plurality of different axes (6 axes)
(i.e., the plurality of classified vibrations generated in the tub
3 according to a plurality of different axes).
[0190] In other words, the controller 60 may calculate information
of the plurality of phase differences between the plurality of
vibration displacement values using the plurality of vibration
displacement values.
[0191] The information of the plurality of phase differences may
include information regarding phase differences between any one
(e.g., Ry vibration) of the plurality of vibrations (Fx vibration,
Fy vibration, Fz vibration, Rx vibration, Ry vibration, and Rz
vibration) and the remaining vibrations (Fx vibration, Fy
vibration, Fz vibration, Rx vibration, and Rz vibration).
[0192] In other words, the information of the plurality of phase
differences may mean to include information regarding phase
differences between any one (e.g., Ry vibration displacement value)
of the plurality of vibration displacement values (Fx vibration
displacement value, Fy vibration displacement value, Fz vibration
displacement value, Rx vibration displacement value, Ry vibration
displacement value, and Rz vibration displacement value) and the
remaining vibration displacement values (Fx vibration displacement
value, Fy vibration displacement value, Fz vibration displacement
value, Rx vibration displacement value, and Rz vibration
displacement value).
[0193] When the any one vibration, a reference vibration, is the Ry
vibration (or Ry vibration displacement value), the information of
the plurality of phase differences may include information of a
phase difference between the front forward-backward and the rear
left-right (phase difference between Fx and Ry), between the front
left-right and the rear left-right (phase difference between Fy and
Ry), between the front up-down and rear left-right (phase
difference between Fz and Ry), between the rear front-rear and the
rear left-right (phase difference between Rx and Ry), and between
the rear up-down and the rear left-right (phase difference between
Rz and Ry), respectively.
[0194] The controller 60 may determine the any one vibration of the
plurality of vibrations (e.g., any one vibration used as a
reference for obtaining a phase difference) based on the location
at which the vibration sensor 77 is disposed.
[0195] For example, when the vibration sensor 77 is located at the
rear R of the tub 3, as illustrated in FIG. 6, the controller 60
may determine any one of vibrations measured from the rear (Rx
vibration, Ry vibration, and Rz vibration) as the reference
vibration.
[0196] Although not illustrated in the drawing, when the vibration
sensor 77 is located at the front F of the tub 3, the controller 60
may select any one of vibrations (Fx vibration, Fy vibration, and
Fz vibration) measured from the front as the reference
vibration.
[0197] Here, the controller 60 may determine, for example, any one
vibration with the largest vibration displacement value among
vibrations measured from the rear (or vibrations measured from the
front when the vibration sensor 77 is disposed at the front of the
tub) as the reference vibration.
[0198] Alternatively, the controller 60 may determine any one
vibration with the largest vibration displacement value among the
measured vibration displacement values (Fx, Fy, Fz, Rx, Ry, and Rz
vibration displacement values) as the reference vibration.
[0199] Alternatively, the controller 60 may determine any one
vibration with the smallest vibration displacement value among the
measured vibration displacement values (Fx, Fy, Fz, Rx, Ry, and Rz
vibration displacement values) as the reference vibration.
[0200] Alternatively, the controller 60 may determine any one
vibration as the reference vibration according to a user's
setting.
[0201] Referring to FIG. 7, the phase difference information may
mean information regarding a time difference between a plurality of
vibrations generated in a plurality of axes. That is, the phase
difference (difference of phase) may mean a time difference between
vibrations.
[0202] For example, the phase difference between Fx and Ry may mean
a time difference between a vibration generated in the front
forward-backward (Fx) axis and a vibration generated in the rear
left-right (Ry) axis, based on the vibration of the rear left-right
(Ry) axis.
[0203] For example, as illustrated in FIG. 7, the phase difference
between Fx and Ry may mean a time difference between the FX
vibration's point of origin and the Ry vibration's point of origin,
based on the Ry vibration's point of origin.
[0204] In this disclosure, any one vibration used as a reference
for expressing phase difference information is placed at the end,
and the other vibration used as a target for comparison (or a
target to be measured) is put before the reference vibration. That
is, the phase difference between Fx and Ry may mean a phase
difference between a Fx (front forward-backward) vibration and a Ry
(rear left-right) vibration based on the Ry vibration.
[0205] It should be noted that an expression of the phase
difference is not absolute. Also, although it may be expressed
differently depending on what is used as a reference vibration, a
physical meaning may be the same.
[0206] The controller 60 may measure a plurality of vibration
displacement values for a plurality of vibrations measured from a
plurality of axes, respectively. In addition, the controller 60 may
calculate (determine) information of a plurality of phase
differences between the plurality of vibrations measured based on
the plurality of axes.
[0207] When the number of the plurality of axes is `n`, the number
of the plurality of vibration displacement values may be equal to
the number of the plurality of axes `n`, and the information of the
plurality of phase differences may be one less than the number of
the plurality of axes `n-1`. This is because information of the
phase difference is calculated based on any one of the
vibrations.
[0208] In addition, the controller 60 may calculate the rotational
speed variation value (RPM variation value), as described above
with reference to FIGS. 4(a)-(b).
[0209] The rotational speed variation value may be calculated based
on, for example, rotational speed values of the drum 4 sensed by
the speed sensing unit 74.
[0210] As described above, unbalance (UB) occurs when the load of
laundry is unevenly distributed in the drum 4. So even if the
controller 60 controls the drum 4 to rotate at the rotational speed
of the detection section (108 RPM), the rotational speed of the
drum 4, as shown in FIGS. 4(a)-(b), may actually be variable (or
fluctuate) without being constantly maintained.
[0211] The controller 60 may calculate (determine) the rotational
speed variation value based on an actual rotational speed of the
drum 4 measured by the speed sensing unit 74. Here, the rotational
speed variation value may be used to calculate a UB value or may be
a UB value itself.
[0212] Thereafter, the controller 60 according to the present
disclosure may calculate a predicted value of the maximum vibration
displacement expected to be generated in the tub 3 by using
measured values (S520).
[0213] The measured values may include the plurality of vibration
displacement values and the information of the plurality of phase
differences as described above. In addition, the measured values
may further include a rotational speed variation value.
[0214] The controller 60 may input at least one of the plurality of
vibration displacement values, the information of the plurality of
phase differences, and the rotational speed variation value as an
input value of the pre-trained ANN to calculate a predicted value
of the maximum vibration displacement as an output value.
[0215] In the present disclosure, it may include an ANN for
calculating a predicted value of the maximum vibration displacement
expected to be generated in the entire dewatering process as a
result value. Information regarding the ANN may be pre-stored in
the memory 78 or the controller 60.
[0216] Here, the maximum vibration displacement is, generally,
generated in the transient section where the drum 4 is rotated at
150 to 600 RPM. The maximum vibration displacement generated in the
entire dewatering process may mean the maximum vibration
displacement generated in the transient section.
[0217] As illustrated in FIG. 8, the controller 60 may input a
plurality of vibration displacement values (Fx vibration
displacement value, Fy vibration displacement value, Fz vibration
displacement value, Rx vibration displacement value, Ry vibration
displacement value, and Rz vibration displacement value) measured
by the vibration sensor 77 in the detection section (section where
the drum 4 is rotated at the specific rotational speed of 108 RPM),
information of a plurality of phase differences (phase difference
between Fx and Ry, phase difference between Fy and Ry, phase
difference between Fz and Ry, phase difference Rx and Ry, and phase
difference between Rz and Ry), and a rotational speed (RPM)
variation value as input layers of a pre-trained ANN.
[0218] The pre-trained ANN may consist of a Long-Short-Term Memory
(LSTM) layer using a LSTM network and a dense layer as shown in
FIG. 8.
[0219] The pre-trained ANN may be a neural network learned to
detect (predict) three-dimensional UB (3D UB) caused by laundry
unevenly distributed in the drum 4, and calculate a predicted value
of the maximum vibration displacement to be generated
accordingly.
[0220] As illustrated in FIG. 8, when the plurality of vibration
displacement values measured in the detection section (108 RPM),
the information of the plurality of phase differences, and the
rotational speed variation value are entered as the input layers,
the pre-trained ANN may output predicted values of the maximum
vibration displacement expected to be generated in the entire
sections of the dewatering process (or the transient section (the
section in which the drum rotates at 150 to 600 RPM)) as output
layers.
[0221] The pre-trained ANN may be a machine-learned neural network
trained to collect input layers of various loads (six displacement
values, five phase difference values and one rotational speed
variation value) and corresponding output layers (six predicted
values of the maximum vibration displacement) through a preliminary
experiment.
[0222] It should be noted that a kind and the number of input
layers and output layers shown in FIG. 8 are just one example, and
are not limited thereto.
[0223] In the pre-trained ANN according to the present disclosure,
at least some of the input values shown in FIG. 8 may be omitted or
added, and at least some of the output values may be omitted or
added.
[0224] That is, an `input` and `output` of the neural network are
just one exemplary embodiment. Smaller input and output layers may
also be used, or a new input parameter and a necessary output
factor may be added as necessary.
[0225] Deep learning is an algorithm that mimics the human brain,
which means to learn by finding a pattern that humans can't
directly find.
[0226] The pre-trained ANN means a neural network learned through
deep learning.
[0227] Deep learning, a class of machine learning, may mean to
learn deep down to multi-levels based on data.
[0228] Deep learning may represent a set (collection) of machine
learning algorithms that extract key data from multiple data by
going through hidden layers in order.
[0229] In the present disclosure, when predicting 3D UB in
dewatering (e.g., when determining (calculating) a predicted value
of the maximum vibration displacement), a LSTM (Long-Short-Term
Memory) network, which is one of the best performing networks among
machine learning based networks developed to date, may be used.
[0230] The LSTM network may include a forget gate for deleting the
past, an input gate for storing current information, and an output
gate for a final result.
[0231] Meanwhile, the network of the pre-trained ANN according to
the present disclosure is not limited to the LSTM network, and
other networks may also be used for prediction.
[0232] For example, the pre-trained ANN used to calculate the
predicted value of the maximum vibration displacement may be
constructed as a Deep Neural Network (DNN) such as a Convolutional
Neural Network (CNN), a Recurrent Neural Network (RNN), a Deep
Belief Network (DBN), and the like, or may be constructed as a
single neural network for one output.
[0233] A method for performing 3D UB deep learning by the
controller 60 is illustrated in FIG. 9. Referring to FIG. 9, the
controller 60 may predict 3D UB by inputting measured values into
the pre-trained ANN after parsing and normalizing the measured
values (e.g., a plurality of vibration displacement values,
information of a plurality of phase differences, and a rotational
speed variation value).
[0234] Here, predicting the 3D UB means that predicting excessive
vibration expected to be generated during the dewatering process.
In order to predict this, the controller 60 may determine
(calculate) a predicted value of the maximum vibration displacement
to be generated during the dewatering process through the
pre-trained ANN.
[0235] Thereafter, when the predicted value of the maximum
vibration displacement is larger than a predetermined reference
value, the controller 60 may predict (determine) that excessive
vibration will occur.
[0236] Meanwhile, the controller 60 may use actually measured
maximum vibration displacement values and the measured values to
train (i.e., update) the pre-trained ANN once again (Deep Network
(Training process) and parameter learning)
[0237] For example, the pre-trained ANN may include an input layer,
a hidden layer, and an output layer. Having multiple hidden layers
is referred to as a Deep Neural Network (DNN). Each layer has a
plurality of nodes, and each layer is connected to the next layer.
Nodes may be interconnected with weights.
[0238] An output from any node belonged to a first hidden layer
(Hidden Layer 1) may be input to at least one node belonged to a
second hidden layer (Hidden Layer 2). In this case, an input of
each node may be a value obtained by applying a weight to a node of
the previous layer. The weight may mean link strength between
nodes. The deep learning process may be seen as a process of
finding proper weights.
[0239] The ANN applied to the washing machine according this
embodiment may be a DNN learned through supervised learning using
the measured values (e.g., the plurality of vibration displacement
values, the information of the plurality of phase differences, and
the rotational speed variation value) as input data, and the
maximum vibration displacement value measured through an experiment
(or actually measured maximum vibration displacement value) as
result data.
[0240] The supervised learning may refer to one method of machine
learning for deriving a function from training data.
[0241] The ANN according to this embodiment may be a DNN in which
hidden layers are trained by inputting measured values (e.g., the
plurality of vibration displacement values, the information of the
plurality of phase differences, and the rotational speed variation
value) as input data, and inputting a maximum vibration
displacement value as a result value. Here, "training the hidden
layers" may mean adjusting (updating) the weights of inter-node
connection lines included in the hidden layers.
[0242] Using this ANN, the controller 60 according to this
embodiment may use values (e.g., the plurality of vibration
displacement values, the information of the plurality of phase
differences, and the rotational speed variation value) measured in
the detection section (section where a rotational speed of the drum
4 is maintained at the specific rotational speed of 108 RPM) as
input values (layers) of the ANN, so as to calculate (predict,
determine, and estimate) a predicted value of the maximum vibration
displacement expected to be generated in the dewatering
process.
[0243] The controller 60 may perform learning by using the measured
values (e.g., the plurality of vibration displacement values, the
information of the plurality of phase differences, and the
rotational speed variation value) as training data.
[0244] The controller 60 may update a DNN structure such as weight,
bias, and the like whenever recognizing or determining a predicted
value of the maximum vibration displacement (or maximum vibration
displacement value) by adding determined results and a plurality of
types of data entered at that time to a database. Also, the
controller 60 may update the DNN structure such as weight, and the
like by performing a supervised learning process using training
data after a predetermined number of training data is obtained.
[0245] The controller 60 of the washing machine according to this
embodiment may input at least one of the plurality of vibration
displacement values, information of the plurality of phase
differences, and the rotational speed variation value as input
values (layers) of the pre-trained ANN, so as to calculate (or
determine) the predicted value of the maximum vibration
displacement as an output value (layer).
[0246] Referring back to FIG. 5, the controller 60 may determine
whether to initialize the dewatering process at the detection
section based on the determined predicted value of the maximum
vibration displacement determined and the predetermined reference
value (S530).
[0247] For example, the controller 60 may initialize the dewatering
process at the detection section when the determined predicted
value of the maximum vibration displacement exceeds the
predetermined reference value.
[0248] As another example, if the determined predicted value of the
maximum vibration displacement is equal to or less than the
predetermined reference value, the controller 60 may rotate the
drum 4 at a faster rotational speed than that of the detection
section (i.e., moving to the next dewatering section after the
detection section, or continuing to the next dewatering process
after the detection section).
[0249] As described above, the controller 60 may determine
(calculate) a predicted value of the maximum vibration displacement
by inputting at least one of the plurality of vibration
displacement values measured in the detection section where
rotation of the drum 4 is maintained at the specific rotational
speed (108 RPM), the information of the plurality of phase
differences, and the rotational speed variation value as input
values of the pre-trained ANN (3D UB deep learning neural
network).
[0250] The predicted value of the maximum vibration displacement
may mean a maximum vibration value expected to be generated in the
tub 3, and a displacement value of the maximum vibration
(amplitude) to be generated not only in the detection section but
also in the entire dewatering process.
[0251] The maximum vibration occurs in the transient section
(section where the drum 4 is rotated at 150 to 600 RPM) of the
entire dewatering process.
[0252] At the detection section (the section in which the drum 4 is
rotated at the specific rotational speed 108 RPM), the controller
60 may determine (or predict) a displacement value of the maximum
vibration (i.e., a predicted value of the maximum vibration
displacement) expected to be generated in the transient
section.
[0253] The predicted value of the maximum vibration displacement
may be output (calculated) as a result value (or output layer) of
the pre-trained ANN as shown in FIG. 8.
[0254] The predicted value of the maximum vibration displacement
may include a plurality of predicted displacement values of the
maximum vibration expected to be generated in each of the plurality
of different axes (multi-axis).
[0255] In detail, the plurality of predicted values of the maximum
vibration displacement may include a predicted value of the maximum
vibration displacement expected to be generated in the front
forward-backward (Fx) axis Fx_max, a predicted value of the maximum
vibration displacement expected to be generated in the front
left-right (Fy) axis Fy_max, a predicted value of the maximum
vibration displacement expected to be generated in the front
up-down (Fz) axis Fz_max, a predicted value of the maximum
vibration displacement expected to be generated in the rear
forward-backward (Rx) axis (Rx_max), a predicted value of the
maximum vibration displacement expected to be generated in the rear
left-right (Ry) axis Ry_max, and a predicted value of the maximum
vibration displacement expected to be generated in the rear up-down
(Rz) axis Rz_max.
[0256] The number of the plurality of predicted values of the
maximum vibration displacement may correspond to the number of a
plurality of different axes (multi-axis) measured by the vibration
sensor 77. If the number of the plurality of axes is `n`, the
number of the plurality of predicted values of the maximum
vibration displacement may also be `n`.
[0257] The controller 60 may initialize the dewatering process at
the detection section when the determined predicted value of the
maximum vibration displacement exceeds the predetermined reference
value.
[0258] In detail, the controller 60 may compare the determined
predicted value of the maximum vibration displacement with the
predetermined reference value to determine whether to initialize
(terminate) the dewatering process, or to continue the dewatering
process further at the detection section where the drum 4 rotates
at the specific rotational speed (108 RPM).
[0259] Here, when each of the plurality of predicted values of the
maximum vibration displacement (Fx_max, Fy_max, Fz_max, Rx_max,
Ry_max, and Rz_max) are all less than or equal to the predetermined
reference value, the controller 60 may rotate the drum 4 faster
than the specific rotational speed of the detection section (i.e.,
dewatering process may be continued).
[0260] Rotating the drum 4 faster than the specific rotational
speed of the detection section may also mean to perform the main
dewatering process where the drum 4 is rotated at high RPM of 150
to 600 RPM (transient section) or more.
[0261] In addition, the controller 60 may stop (or terminate)
rotation of the drum 4 at the detection section, when at least one
of the plurality of predicted values of the maximum vibration
displacement (Fx_max, Fy_max, Fz_max, Rx_max, Ry_max, Rz_max)
exceeds the predetermined reference value.
[0262] Terminating the rotation of the drum 4 may be included in
the meaning of "initializing the dewatering process". That is, in
this disclosure, initializing the dewatering process may mean that
stopping (terminating) the rotation of the drum 4 to restart the
dewatering process from the step (or section) after detecting the
load or amount of laundry.
[0263] The predetermined reference value may be set for each of the
plurality of different axes (multi-axis, 6-axis).
[0264] For example, a predetermined first reference value may be
set for the front forward-backward (Fx) axis, and a predetermined
second reference value, which is differentiated from the first
reference value, may be set for the front left-right (Fy) axis. In
addition, a third reference value for the front up-down (Fz) axis,
a fourth reference value for the rear forward-backward (Rx) axis, a
fifth reference value for the rear left-right (Ry) axis, and a
sixth reference value for the rear up-down (Rz) axis may be set,
respectively.
[0265] The predetermined reference values set for each of the
plurality of different axes may have the same or different
values.
[0266] The predetermined reference values set for each of the
plurality of different axes may be set based on a gap between the
tub 3 and the cabinet 1.
[0267] For example, if a gap between an origin point of the front
forward-backward (Fx) axis and the cabinet is 11 mm, the first
reference value set for the front forward-backward (Fx) axis may be
less than 11 mm.
[0268] When the predicted values of the maximum vibration
displacement determined (calculated) for the plurality of different
axes do not exceed (equal to or lower than) the respective
predetermined reference values, the controller 60 may rotate the
drum 4 faster than the specific rotational speed of the detection
section (i.e., the dewatering process may be performed at high
RPM).
[0269] On the other hand, when at least one of the predicted values
of the maximum vibration displacement determined (calculated) for
the plurality of different axes exceeds the respective
predetermined reference value (for example, when Fx_max exceeds the
first reference value set for the Fx axis), the controller 60,
without increasing the rotational speed of the drum 4 at the
detection section, may initialize the dewatering process (i.e.,
terminate (stop) the rotation of the drum 4, and restart the
dewatering process from the step (or section) after detecting the
load of laundry.
[0270] FIGS. 10 and 11 are result data of experiments employing a
control method according to an embodiment of the invention.
[0271] FIG. 10 shows experiment results of a correlation between
predicted values of the maximum vibration displacement (Fx_max,
Fy_max, Ry_max) calculated by a pre-trained ANN according to an
embodiment and values of the maximum vibration displacement
measured through an experiment.
[0272] When vibration is measured based on the existing UB signal
(UB value, rotational speed variation value), a correlation
coefficient of the two is 0.5 or less. On the other hand, when
vibration is measured using the pre-trained ANN employing 3D UB
deep learning, a correlation coefficient of the two is 0.8 or more,
showing a stronger correlation.
[0273] As such, in the present disclosure, a plurality of vibration
displacement values measured by the vibration sensor 77,
information of a plurality of phase differences, and a rotational
speed variation value are entered into the ANN pre-trained by 3D UB
deep learning to output a predicted value of the maximum vibration
displacement (result value). The predicted value of the maximum
vibration displacement has a pretty strong correlation with a
maximum vibration displacement value actually measured, thereby
significantly increasing accuracy of predicting excessive
vibration.
[0274] In addition, it can be seen that data of the predicted value
of the maximum vibration displacement determined (calculated) using
the ANN pre-trained by 3D UB deep learning is highly reliable.
[0275] FIG. 11 shows experiment results of a dewatering entry time
and the maximum vibration displacement of the drive unit (tub with
drum) in which the ANN pre-trained by 3D UB deep learning according
to the present disclosure is applied to determine whether to
initialize the dewatering process at the detection section, or to
continue the dewatering process.
[0276] It is understood that there is a substantial decrease in the
dewatering entry time compared to the existing product (e.g., when
a UB signal is only considered), when the predetermined reference
value of each of the plurality of axes, used as a comparison with a
predicted value of the maximum vibration displacement, is set
within a range (value) for preventing the tub 3 and the cabinet 1
from colliding with each other.
[0277] Here, the dewatering entry time may be time required to
enter the process of dewatering while the drum 4 is rotated faster
than that of the detection section (section where the drum 4
rotates at the specific rotational speed (108 RPM)), that is, time
required for entering the main dewatering process, or high-speed
dewatering process.
[0278] Here, a condition D of the maximum vibration displacement of
the drive unit is that the existing UB detection criterion (or
reference) is set to be excessively low. As for the experiment
result of the present disclosure employing 3D UB deep learning, in
order to reduce the dewatering entry time, the predetermined
reference value, which is compared with a prediction value of the
maximum vibration displacement, is loosened (the predetermined
reference value is set as large as possible within a range not to
make the tub collide with the cabinet).
[0279] The washing machine according to the present disclosure may
set a reference value (i.e., a reference limit of displacement)
according to each of the plurality of axes (multi-axis, each
vibration direction) by considering a gap between the drive unit
(tub with drum) and the cabinet, so as not to collide with each
other with respect to the different plurally of axes.
[0280] At the detection section where the drum 4 is rotated at the
specific rotational speed (108 RPM), if any one of the predicted
values of the maximum vibration displacement calculated or
determined by 3D UB deep learning exceeds the predetermined
reference value, the controller 60 may stop the rotation of the
drum 4, so that the dewatering process is restarted (initialized)
after detecting the load of laundry.
[0281] Here, predicting the maximum vibration displacement through
3D UB deep learning, as described above, may mean that a plurality
of vibration displacement values for the plurality of different
axes measured by the vibration sensor 77, information of the
plurality of phase differences between a plurality of vibrations
detected from the plurality of axes, and a rotational speed
variation value are entered as input values of the pre-trained ANN
to determine (calculate, output) a predicted value of the maximum
vibration displacement for each of the plurality of axes as result
values.
[0282] In addition, the predicted value of the maximum vibration
displacement may mean a displacement value of the maximum vibration
expected to be generated in the entire dewatering process (or
transient section), not just limited to the detection section.
[0283] Thereafter, when all predicted values of the plurality of
the different axes do not exceed the respective predetermined
reference values, the controller 60 may proceed with the main
dewatering process in which the drum 4 is rotated faster than the
specific rotational speed (108 RPM) of the detection section.
[0284] In addition, when at least one of the predicted values of
the maximum vibration displacement determined (calculated) for each
of the plurality of different axes exceeds the respective
predetermined reference value, the controller 60 may stop the
rotation of the drum 4 and perform initializing (or terminating)
the dewatering process to restart the dewatering process from the
step after detecting the load of laundry.
[0285] With this configuration, it may prevent the dewatering
process from being initialized, caused by a vibration value
exceeding the reference value, in the middle of dewatering after
having passed the detection section, thereby reducing time required
for dewatering and preventing excessive vibration from
occurring.
[0286] In addition, according to the embodiments disclosed herein,
power consumption may be reduced by preventing the dewatering
process from being initialized in a state that the rotational speed
(RPM) of the drum 4 is increased after the detection section.
[0287] Further, according to the embodiments disclosed herein, an
occurrence of abnormal vibration (excessive vibration) at the
resonance section (transient section, 150 to 600 RPM) may be
accurately predicted using a large amount of information (12 pieces
of information, in total) based on deep learning, compared to the
conventional methods using limited information, which is based on
information prior to resonance generated in the transient
section.
[0288] The excessive vibration described herein refers to a large
vibration (e.g., vibration having the maximum vibration
displacement value greater than the predetermined refence value)
which is large enough to make the drive unit (tub with drum)
collide with the cabinet.
[0289] The present disclosure directly predicts whether excessive
vibration is generated based on the predicted value of the maximum
vibration displacement using the pre-trained ANN, thereby
increasing prediction accuracy significantly.
[0290] In addition, according to the embodiments disclosed herein,
an AI dewatering algorithm may be provided to more accurately
determine whether to initialize the dewatering process in a low RPM
section (e.g., 108 RPM or less) before entering a high RPM section
(e.g., 150 RPM or more, or the transient section (resonance
section)).
[0291] The effects of the embodiments disclosed herein include but
are not limited to the following:
[0292] One, the maximum vibration displacement expected to be
generated during a dewatering process is predicted at a detection
section, thereby determining whether to initialize the dewatering
process, or to continue the dewatering process at the beginning of
dewatering.
[0293] Two, unbalance (UB) that causes excessive vibration to occur
may be detected at an early stage of the dewatering process,
allowing the dewatering process to be initialized early. As a
result, time required for dewatering can be reduced.
[0294] Three, when a predicted value of the maximum vibration
displacement, which is calculated in the detection section by an
ANN, exceeds a preset reference value, the dewatering process is
initialized (or stopped) without continuing the dewatering process
further, thereby preventing excessive vibration from occurring and
decreasing time taken to enter the dewatering process.
[0295] The effects of the present disclosure are not limited to
those effects mentioned above, and other effects not mentioned may
be clearly understood by those skilled in the art from the
description of the appended claims.
[0296] The above description may also be equally or similarly
applied to a method for controlling a washing machine. The method
of controlling the washing machine may be performed by, for
example, the controller 60.
[0297] The present disclosure described above can be implemented as
computer-readable codes on a program-recorded medium. The computer
readable medium includes all kinds of recording devices in which
data readable by a computer system is stored. Examples of such
computer-readable media may include hard disk drive (HDD), solid
state disk (SSD), silicon disk drive (SDD), ROM, RAM, CD-ROM,
magnetic tape, floppy disk, optical data storage element and the
like. The computer may include the processor or the controller.
[0298] Although preferred embodiments have been depicted and
described in detail herein, it will be apparent to those skilled in
the relevant art that various modifications, additions,
substitutions and the like can be made without departing from the
spirit of the disclosure, and these are, therefore, considered to
be within the scope of the disclosure, as defined in the following
claims.
* * * * *