U.S. patent application number 16/869338 was filed with the patent office on 2021-11-11 for air filter condition sensing.
This patent application is currently assigned to 3M INNOVATIVE PROPERTIES COMPANY. The applicant listed for this patent is 3M INNOVATIVE PROPERTIES COMPANY. Invention is credited to Jonathan B. Arthur, Karl W. Bloedorn, Jayant Chakravarty, Douglas D. Fletcher, Dennis M. Glass, Eric O. Hemberg, Oscar M. Hemberg, Daniel W. Hennen, Lyle L. Luppes, Michael A. Meis, Gene B. Portelli.
Application Number | 20210346833 16/869338 |
Document ID | / |
Family ID | 1000005925996 |
Filed Date | 2021-11-11 |
United States Patent
Application |
20210346833 |
Kind Code |
A9 |
Arthur; Jonathan B. ; et
al. |
November 11, 2021 |
AIR FILTER CONDITION SENSING
Abstract
An air filter includes filter media, a sensor, and circuitry
coupled to the sensor, the circuitry configured to receive data
from the sensor representative of the condition of the filter media
and wirelessly transmit such data. The data may be received by a
device with a display to use the information to present an
indication of the filter media condition to a user.
Inventors: |
Arthur; Jonathan B.;
(Hudson, WI) ; Bloedorn; Karl W.; (Oakdale,
MN) ; Chakravarty; Jayant; (Woodbury, MN) ;
Portelli; Gene B.; (Lake Elmo, MN) ; Glass; Dennis
M.; (Cottage Grove, MN) ; Meis; Michael A.;
(Stillwater, MN) ; Luppes; Lyle L.; (Rosemount,
MN) ; Hennen; Daniel W.; (Cottage Grove, MN) ;
Fletcher; Douglas D.; (Woodbury, MN) ; Hemberg; Eric
O.; (Shatin, HK) ; Hemberg; Oscar M.; (Dalaro,
SE) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
3M INNOVATIVE PROPERTIES COMPANY |
St. Paul |
MN |
US |
|
|
Assignee: |
3M INNOVATIVE PROPERTIES
COMPANY
|
Prior
Publication: |
|
Document Identifier |
Publication Date |
|
US 20200391151 A1 |
December 17, 2020 |
|
|
Family ID: |
1000005925996 |
Appl. No.: |
16/869338 |
Filed: |
May 7, 2020 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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16438803 |
Jun 12, 2019 |
10646809 |
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16869338 |
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15876742 |
Jan 22, 2018 |
10363509 |
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16438803 |
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PCT/US2017/045508 |
Aug 4, 2017 |
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15876742 |
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62374040 |
Aug 12, 2016 |
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62372156 |
Aug 8, 2016 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
H04W 4/38 20180201; B01D
46/446 20130101; B01D 46/429 20130101; G01L 13/00 20130101; B01D
46/10 20130101; B01D 46/0086 20130101; H04W 4/80 20180201; H04W
4/33 20180201; G01L 19/086 20130101; B01D 46/521 20130101 |
International
Class: |
B01D 46/00 20060101
B01D046/00; B01D 46/52 20060101 B01D046/52; H04W 4/38 20060101
H04W004/38; H04W 4/33 20060101 H04W004/33; G01L 19/08 20060101
G01L019/08; G01L 13/00 20060101 G01L013/00; H04W 4/80 20060101
H04W004/80; B01D 46/44 20060101 B01D046/44; B01D 46/42 20060101
B01D046/42; B01D 46/10 20060101 B01D046/10 |
Claims
1. An air filter comprising: filter media comprising a downstream
side and an upstream side; a pressure sensor attached to only one
side of the filter media; and circuitry coupled to the sensor, the
circuitry configured to receive pressure data from the sensor
representative of the condition of the filter media and wirelessly
transmit such data, wherein the sensor does not rely on the
monitoring of airflow through a bypass through or around the filter
media.
2. The air filter of claim 1, wherein the circuitry is adapted to
transmit sensor data to a memory device coupled to a processor and
having a program stored thereon for execution by the processor to
determine a pressure at the filter media as a function of the data
from the pressure sensor.
3. The air filter of claim 2, wherein the processor is programmed
to determine a status of the filter by a temporal analysis of the
pressure data.
4. The air filter of claim 1, wherein the circuitry or the
processor is adapted to determine a pressure difference across the
filter media as a function of the data from the pressure
sensor.
5. The air filter of claim 1 and further comprising a second sensor
to provide second data, wherein the circuitry is further adapted to
combine the second data with the data from the pressure sensor to
determine a pressure or pressure difference.
6. The air filter of claim 1 and further comprising an
electronically readable filter ID, wherein the circuitry is further
adapted to at least one of read the filter ID and transmit the
filter ID, and wherein the circuitry is adapted to use the filter
ID to enable or disable providing wireless data transmission.
7. The air filter of claim 1, wherein the pressure sensor is
attached to the downstream side of the filter media.
8. The air filter of claim 7, wherein the pressure sensor is an
absolute pressure sensor.
9. The air filter of claim 1, wherein the circuitry is further
adapted to generate an alert indicative of a time to replace the
air filter as a function of the sensed condition of the filter.
10. The air filter of claim 1, wherein the sensor is releasably
coupled to the filter media.
11. The air filter of claim 1, wherein the sensor is co-located
with the circuitry in a sensor housing, and wherein the sensor
housing is adhered to the filter media.
12. A system for determining the useful life of an air filter, the
system comprising: An air filter comprising: filter media
comprising a downstream side and an upstream side; an absolute
pressure sensor attached to only one side of the filter media and
adapted to measure downstream pressure while air is moved through
the filter media; and circuitry coupled to the sensor, the
circuitry configured to receive pressure data from the sensor
representative of the condition of the filter media and wirelessly
transmit such data, wherein the sensor does not rely on the
monitoring of airflow through a bypass through or around the filter
media; and a personal mobile device comprising a processor; a
display coupled to the processor; and a memory device coupled to
the processor and having a program stored thereon for execution by
the processor to perform operations comprising: wirelessly
receiving data directly or indirectly from the sensor
representative of a condition of filter media; providing a visual
indication to a user on the display representative of the condition
of the filter media as a function of the received data, wherein the
visual indication includes a graphical representation of a
remaining period of useful life of the filter media.
13. The system of claim 12, wherein the operations further comprise
generating a filter type recommendation based on user profile
information indicative of air quality.
14. The system of claim 12, wherein the circuitry is co-located
with the sensor in a sensor housing, and wherein the sensor housing
is affixed to the filter media.
15. The system of claim 12, wherein the operations further comprise
obtaining time-based pressure data points from the sensor;
calculating a mean difference between obtained adjacent pressure
data points; and estimating filter life based on the identification
of a pressure difference in adjacent points that is greater than a
threshold pressure difference.
16. The system of claim 12, wherein the user profile information is
indicative of a medical condition correlated to air quality.
17. The air filter of claim 1, wherein the sensor comprises a
single pressure sensor attached to only the downstream side of the
filter media.
18. A method of maintaining a heating cooling and ventilation
(HVAC) system, the method comprising providing an air filter in the
HVAC system, the air filter comprising filter media comprising a
downstream side and an upstream side; a pressure sensor directly
attached to only one side of the filter media adapted to measure
pressure while air is moved through the filter media; and circuitry
coupled to the sensor, the circuitry configured to receive pressure
data from the sensor representative of the condition of the filter
media and wirelessly transmit such data, wherein the sensor does
not rely on the monitoring of airflow through a bypass through or
around the filter media; receiving an indication from a personal
mobile device that the air filter is at or near the end of its
useful life, the indication based on the condition of the filter
media as a function of the pressure data transmitted; and removing
the filter from the HVAC system.
19. The method of claim 18, wherein the indication is presented on
a display on the personal mobile device.
20. The method of claim 19, wherein the indication is a visual
indication that includes a graphical representation of a remaining
period of useful life of the filter media.
21. The method of claim 18, wherein providing an air filter
comprises installing an air filter in ductwork.
Description
CROSS REFERENCE TO RELATED APPLICATIONS
[0001] This application is a continuation of U.S. application Ser.
No. 16/438,803, filed Jun. 12, 2019, which is a continuation of
U.S. application Ser. No. 15/876,742, now U.S. Pat. No. 10,363,509,
filed Jan. 22, 2018, which is a continuation of PCT Application
PCT/US2017/045508, filed Aug. 4, 2017, which claims the benefit of
U.S. Provisional Application No. 62/374,040, filed Aug. 12, 2016,
and U.S. Provisional Application 62/372,156, filed Aug. 8, 2016,
the entire contents of which are incorporated herein by
reference.
BACKGROUND
[0002] An air filter may be included in furnaces and stand-alone
air purifiers. Air is drawn through the filter, and the filter
traps particles, preventing them from proceeding through ducts to
environmental spaces that are being heated, cooled, or otherwise
conditioned.
[0003] In-home furnace air filters become ineffective or blocked
over time and need to be replaced to minimize wear on furnace fan
motors as well as to maintain air purification effectiveness and
maintain adequate airflow. Traditional filter obstruction is
defined by the difference in pressure before the filter and after
the filter in respect to airflow. An increase in the difference in
pressure is indicative of the filter becoming more blocked and
needing replacement.
SUMMARY
[0004] An air filter includes filter media, a sensor, and circuitry
coupled to the sensor, the circuitry configured to receive data
from the sensor representative of the condition of the filter media
and wirelessly transmit such data. The data may be received by a
device or system with a display to use the information to present
an indication of the filter media condition to a user.
BRIEF DESCRIPTION OF THE DRAWINGS
[0005] FIG. 1 is a photograph that includes a disposable air filter
according to an example embodiment.
[0006] FIG. 2 is a photograph of a differential pressure sensor to
couple to filter media according to an example embodiment.
[0007] FIG. 3 is a block diagram of a filter with a differential
pressure sensor according to an example embodiment.
[0008] FIG. 4 is an illustration of a simulated user interface of
an application running on a mobile device according to an example
embodiment.
[0009] FIG. 5A is a table indicating blower speed in feet per
minute, differential pressure sensor readings in millibars, duct
pressure, a calculated pressure, and a letter, A, B, or C
correlating results to a graph as shown in FIG. 5B according to an
example embodiment.
[0010] FIG. 5B is a graph that illustrates the calculated pressure
according to an example embodiment.
[0011] FIG. 6 is a graph comparing pressures obtained from a test
with a blower running at different speeds according to an example
embodiment.
[0012] FIG. 7 is a table similar to FIG. 5A according to an example
embodiment.
[0013] FIG. 8 is a graph comparing pressures obtained from a test
with a blower running at different speeds according to an example
embodiment.
[0014] FIG. 9 is a graph showing pressures at different time
intervals according to an example embodiment.
[0015] FIG. 10 is block diagram of a system for sensing obstruction
of an air filter according to an example embodiment.
[0016] FIG. 11 is a block flow diagram illustrating configuration
and use of a mobile device to interact with a filter sensor
according to an example embodiment.
[0017] FIG. 12 is a block diagram of an example system utilizing
two pressure sensors according to an example embodiment.
[0018] FIG. 13 is a block flow diagram illustrating calibration of
pressure sensors according to an example embodiment.
[0019] FIG. 14 provides information regarding an exemplary
temperature and humidity sensor according to an example
embodiment.
[0020] FIG. 15 is a photograph of an experimental system for
testing a smart filter according to an example embodiment.
[0021] FIG. 16 provides representations of data streaming from
smart filter circuitry according to an example embodiment.
[0022] FIG. 17 is photograph of a filter installed in common home
consumer furnace ductwork according to an example embodiment.
[0023] FIG. 18 is a graph illustrating the difference in pressure
across a filter with the fan first off, then on, then off again
according to an example embodiment.
[0024] FIG. 19 is a table indicating information transmitted and
collected during operation of a system including a smart filter
according to an example embodiment.
[0025] FIG. 20 is a graph indicating readings from a single
downstream side pressure sensor with the furnace or fan off, and
then on, where the filter is known to be dirty and in need of
replacement according to an example embodiment.
[0026] FIG. 21 is a block diagram representation of a smart filter
with various options for providing an ID of the filter, sensing the
filter media condition, and optionally sensing air quality
according to an example embodiment.
[0027] FIG. 22 is a block diagram representation of multiple
elements and alternative elements in a smart filter system
according to an example embodiment.
[0028] FIG. 23 is a block flow diagram illustrating the
configuration and use of information from a plurality of sources to
determine filter life according to an example embodiment.
[0029] FIG. 24 illustrates multiple pressure measurements
indicative of differential pressure across a filter under varying
conditions over time according to an example embodiment.
[0030] FIG. 25 illustrates data collected from an accelerometer
sensor measuring vibration in a y-direction in the duct in which
the filter is inserted according to an example embodiment.
[0031] FIG. 26 similarly illustrates measurements of vibration in
an x-direction according to an example embodiment.
[0032] FIG. 27 similarly illustrates measurement of vibration in a
z-direction according to an example embodiment.
[0033] FIG. 28 illustrates accelerometer results with respect to
time in the y-direction according to an example embodiment.
[0034] FIG. 29 illustrates accelerometer results with respect to
time in the x-direction according to an example embodiment.
[0035] FIG. 30 illustrates accelerometer results with respect to
time in the z-direction according to an example embodiment.
[0036] FIG. 31 is a block schematic diagram of a computer system to
implement circuitry and methods according to an example
embodiment.
DETAILED DESCRIPTION
[0037] In the following description, reference is made to the
accompanying drawings that form a part hereof, and in which is
shown by way of illustration specific embodiments which may be
practiced. These embodiments are described in sufficient detail to
enable those skilled in the art to practice the invention, and it
is to be understood that other embodiments may be utilized and that
structural, logical and electrical changes may be made without
departing from the scope of the present invention. The following
description of example embodiments is, therefore, not to be taken
in a limited sense, and the scope of the present invention is
defined by the appended claims.
[0038] The functions or algorithms described herein may be
implemented in software in one embodiment. The software may consist
of computer executable instructions stored on computer readable
media or computer readable storage device such as one or more
non-transitory memories or other type of hardware based storage
devices, either local or networked. Further, such functions
correspond to modules, which may be software, hardware, firmware or
any combination thereof. Multiple functions may be performed in one
or more modules as desired, and the embodiments described are
merely examples. The software may be executed on a digital signal
processor, ASIC, microprocessor, or other type of processor
operating on a computer system, such as a personal computer, server
or other computer system, turning such computer system into a
specifically programmed machine.
[0039] Embodiments are described to identify when an air filter
should be replaced. The embodiments utilize sensors and analytics
to determine if and when replacement is of the air filter is
desired. A network connection may be used to communicate an
indication of filter which should be replaced. The indication may
be provided to a user via an application running on a mobile device
that receives the indication via the network. Information may be
transferred based on a network connection such as a Bluetooth Low
Energy (BLE) connection direction between a sensor and analytics
device associated with the filter, a Wi-Fi connection, ZigBee, or
Zwave for example. An RFID based connection or other connection may
be used to transfer information in further embodiments. The
application may enable ordering of a replacement filter either
automatically or responsive to a user selectable option provided on
the mobile device by the application. The application may also
provide for reading a bar code, QR code, or other information from
a filter and use such information to control use of the sensor on
only specified filters. The information may also be used to
configure the sensors and/or application for an allowed pressure
drop or airflow measurement parameter for a corresponding
filter.
[0040] In one embodiment, a single pressure sensor, or a multitude
of different sensors may be used to identify pressure obstruction
of a filter. The single sensor may be positioned after the filter
on the clean air side between the filter and fan side using a
vacuum phenomenon created by the motor increasing effort as the
filter becomes increasingly obstructed. In other words, the
pressure drops while the fan is running, with the drop being
greater as the filter becomes more obstructed. A threshold, such as
a drop of 2 or more pascals while the fan is on compared to the fan
being off, may be used to trigger customer notifications to replace
the filter in one embodiment.
[0041] In one embodiment, the single pressure sensor provides
pressure readings to analytics software executing on a processor.
The processor and pressure sensor may be formed as an integrated
unit. The integrated unit may also include networking capabilities.
With the use of a single pressure sensor, the sensor may be
calibrated by observing pressure with the fan on and the fan off.
It may then be assumed that the pressure with the fan on is
representative of the pressure difference between sides of the
filter. Several examples of algorithms that utilize sensor data to
generate notifications of filter obstruction are provided
below.
[0042] Feedback may be provided to customers to communicate the
effectiveness of air filtration filters as well as timing to
replace and need to replace data. Previous concepts are susceptible
to clogging by dirty air on the upstream side of the filter. Having
to maintain two sensors also increases the sensor cost for the
consumer. An affordable sensor can be provided to consumers to
assist them in maintaining high air quality standards in their home
through the appropriate servicing of their in-home furnace
filter.
[0043] In a further embodiment, a differential pressure sensor may
be coupled to the filter media with two openings on opposite sides
of the filter media to communicate the pressure on each side to a
differential pressure sensing element, such as a capacitor plate or
piezoelectric element that flexes responsive to the difference in
pressure. The sensing element may be located on one side with a
first opening, with a tube with a second opening extending through
the media to the other side of the media. The openings are disposed
on either side of the differential pressure sensing element.
[0044] In further embodiments, parameters other than pressure may
be measured or sensed and correlated with a filter condition
indicative of a time to replace the filter. Such parameters include
for example, load on the fan motor, airspeed, turbulence,
particulates, optical clarity, vibration, thermoelectric sensor,
strain gage indicative of bending, and others. In still further
embodiments, data from one or more sensors may be fused or
otherwise combined by the analytics software to generate the
indication for filter replacement.
[0045] In some embodiments, the sensor and/or integrated sensor
unit may attach to or be integrated with the filter media, or
attached to a frame of the filter media. The frame may be a
permanent refillable plastic filter frame. In some embodiments, the
unit may be attached to filter media or a frame of the filter and
reused by removing the unit and attaching the unit to a replacement
filter, filter frame, or filter media. The unit may also be
attached to a frame of a filter having replaceable filter
media.
[0046] FIG. 1 is a photograph that includes a disposable air filter
100. The filter 100 may have a generally rectangular shape (which
includes square shapes). Disposable filter 100 may comprise an
upstream face 101 (facing away and not visible) and a downstream
face 102, and may comprise a filter media 107 surrounded by an
optional perimeter frame 103. The filter media 107 may be
replaceable by removing the filter media from the frame and
replacing the filter media with new or reconditioned filter media.
In further embodiments, the filter media may be self-supporting
without a frame if formed with sufficient structural integrity to
maintain an effective shape for filtering air when subjected to
airflow. In various embodiments, filter media 107 may be pleated so
as to exhibit readily identifiable pleats 108, or, it may be
unpleated. In one embodiment, a sensor 110, such as a pressure
sensor is supported by the filter. The sensor 110 may include
electronics to process and communicate sensor readings indicative
of filter media condition. The sensor may be supported by a hanging
structure as shown at 110 in FIG. 1 or affixed directly to the
filter media or frame.
[0047] Perimeter frame 103 may often comprise sidewalls (e.g., top,
bottom, left and right sidewalls) 104 that define terminal edges of
the framed filter. Frame 103 may be made of any suitable
material(s), e.g., paperboard or cardboard that may be folded to
provide the various sidewalls. In some embodiments, the frame 103
may be made of an injection molded plastic material. In some
embodiments, at least the downstream face 102 of filter 100 may
comprise support members that extend at least partially across
filter media 107 (in any direction). Such members may provide
additional support, particularly on the downstream side of the
filter media; and (particularly for pleated filter media), such
members may assist in minimizing or ensuring consistency of
deformation of the filter media in response to air pressure during
operation of the room air purifier. In some embodiments such
members may be strips of paperboard that may be connected to frame
103 at their terminal ends. In other embodiments such members may
be lengths of adhesive strands. If the filter media is pleated, any
such adhesive strands may be deposited either before or after the
filter media is pleated.
[0048] Many different types of filter styles with various pleating
options may be used. For example, mini-pleat designs may use wire
affixed to the pleat tips on one or both sides of the filter. Micro
pleat designs may use wire on one side of filter media where the
wire is contoured to the pleating of the media to maintain the
pleat shape. Flat panel filter media may use wire and/or polyolefin
netting. Some filter designs may use polyolefin strands versus
adhesive strands to maintain pleat spacing.
[0049] The filter media 107 (whether pleated or not) of a
disposable air filter 100 may be comprised of nearly any material,
in any configuration, that is capable of filtering moving air. Such
media may include, but is not limited to, fibrous materials (e.g.,
nonwoven webs, fiberglass webs, and so on), honeycomb structures
loaded with filter media and/or sorbent material, and so on. In
particular embodiments, the filter media may include at least one
layer that comprises at least some material that can be
electrically or electrostatically charged to form an electret
material. In particular embodiments, the filter media may be a
multilayer media that comprises at least one layer that includes an
electret material, and at least one layer that includes a sorbent
material. In some embodiments filter media 107 may comprise at
least one layer capable of HEPA filtration. Electrostatically
charged media may enhance particulate capture. Electrically charged
media may be used in electrostatic precipitators which have a
current and ground wire and are typically washable.
[0050] If at least one layer of the filter media 107 is to exhibit
sorbent functionality, any suitable sorbent(s), in any convenient
physical form, may be included in such a layer. In particular
embodiments, such a sorbent may be capable of capturing
formaldehyde (formaldehyde is a very light gas which may not be
captured by typical carbon filters. Many carbon filters capture
much heavier gases such as urea, cooking odors, etc. These filters
use activated carbons. To capture Formaldehyde and toluene gases, a
treated (often acid treated) carbon may be used. In some
embodiments, the sorbent includes at least some activated carbon.
If desired, the activated carbon may be treated to enhance its
ability to capture formaldehyde. Suitable treatments may e.g.,
provide the activated carbon with at least some amine functionality
and/or at least some manganate functionality and/or at least some
iodide functionality. Specific examples of treated activated
carbons that may be suitable include those that have been treated
with e.g., potassium permanganate, urea, urea/phosphoric acid,
and/or potassium iodide. Other sorbents that may be potentially
suitable e.g., for removing formaldehyde include e.g., treated
zeolites and treated activated alumina. Such materials may be
included e.g., along with treated activated carbon if desired.
[0051] The one or more sorbents may be provided in any usable form;
for example as particles, which may be, e.g., powder, beads,
flakes, whiskers, granules or agglomerates. The sorbent particle
size may vary as desired. The sorbent particles may be incorporated
into or onto a layer of filter media 107 in any desired fashion.
For example, in various embodiments the sorbent particles may be
physically entangled with fibers of a layer of filter media 107,
may be adhesively bonded to such fibers, or some combination of
both mechanisms may be used.
[0052] In one embodiment, disposable air filter 100 may include at
least one RFID (radiofrequency identification) tag 120. In some
embodiments, an RFID tag 120 may be mounted to any portion of a
perimeter frame 103 of air filter 100. For example, an RFID tag 120
may be mounted to an interior major surface of a sidewall of the
frame, or to an exterior or interior (i.e., visible or not visible)
major surface of an upstream or downstream flange of the frame. In
some embodiments, RFID tag 120 is mounted to (e.g., attached to,
e.g., adhesively attached to) a major outward surface of a sidewall
104 of perimeter frame 103 of disposable air filter 100. RFID tag
120 may be any suitable RFID tag. In many embodiments, RFID tag 120
may be a passive tag, meaning that it does not include any kind of
power source and is solely powered by the electromagnetic energy
that is impinged upon it by the RFID reader. In some embodiments,
RFID tag 120 may be a conventional RFID tag (operating e.g., at
high, medium or low frequency) whose range is not particularly
limited. In particular embodiments, RFID tag 120 may be a so-called
Near Field Communication (NFC) tag, which will be recognized by the
skilled person as being a particular type of RFID tag that operates
(e.g., at 13.56 MHz) only over the range of a few (e.g., ten or
less) centimeters. In some embodiments RFID tag 120 is a readable
(only) tag; in other embodiments it may be a readable/writeable tag
as discussed in detail later herein. In some embodiments, RFID tag
120 may conveniently be supplied with an adhesive backing so that
RFID tag 120 can be quickly and easily installed onto a surface of
a sidewall 104 of a frame of filter 100.
[0053] In one embodiment, a single differential pressure sensor may
be used and encased in a small plastic housing 200 as indicated in
FIG. 2. The housing 200 may include one or more sensors to measure
the differential pressure, processing electronics and Bluetooth Low
Energy communication electronics. The pressure sensor(s) measures
pressure drop of the filter to determine the filter's performance
and when it should be replaced (i.e., the end of life for the
filter).
[0054] In one embodiment, the housing 200 includes a tube 210 that
is adapted to be pressed through the filter material from the fan
side of the filter to provide a first opening 212 in the side of
the filter receiving air to be filtered. In one embodiment, the
tube 210 may be formed as a small sharp port that is used to
puncture the filter media. A cap or locking nut 215 may fit over
the tube and snap fit, friction fit, screw, or otherwise retain the
housing in place to the filter while allowing communication of
pressure via the first opening to one side of the differential
pressure sensor within housing 200.
[0055] In some embodiments, the housing 200 with sensor or sensors
may be reused on a new filter or filter media by removing the
locking nut 215, removing the rest of the housing 200 from the
filter and repeating installation on a new filter or filter media
in the case of a filter frame allowing replacement of filter media.
The housing with sensor or sensors may be installed on a filter
frame and optionally reused.
[0056] A second opening, not shown, is positioned on the other side
of housing 200 to provide communication of pressure from the fan
side of the filter material to the differential pressure sensor
such that the differential pressure sensor measures the pressure
difference between the first and second openings.
[0057] The processing electronics (in this case built into the
sensor ICs) converts the pressure measurements into an electrical
input signal (in this case digital) for the Bluetooth
communications electronics. In further embodiments, the processing
electronics may be expanded to handle signals from other included
sensors that provide air quality measurements (before and/or after
the filter) in a facility or home, filter run time, humidity,
etc.
[0058] The Bluetooth communication electronics transmits the sensor
information to a user's Bluetooth device (i.e., smart phone,
tablet, etc.) so that the user can monitor the filter's performance
and know when to change the filter via one or more applications
running on the device. In addition to monitoring, the
application(s) can be configured to notify the user when it's time
to change the filter. The sensor may be powered by a coin cell
battery. This coin cell battery will be easily replaceable by the
customer. Other types of batteries, including fuel cells and
rechargeable batteries may be used in further embodiments. The
battery voltage level may be displayed and a battery low alert may
be provided to a user to notify a user to change the battery.
[0059] A block diagram of an active air furnace filter sensor 300
is shown in FIG. 3. To prevent sensor clogging a small mechanical
dust cap 305 may be molded onto the sensor nut 215. The dust cap
305 will prevent dust from clogging the sensor port. Sensor 300 may
include a downstream opening 310, which in combination with an
upstream opening 212 provides a pressure differential across a
differential sensor 315, which in one embodiment may include back
to back absolute pressure sensors, or a capacitive plate that
flexes responsive to a difference in pressure across it, changing a
capacitance of a circuit including the plate. A processor 320 may
be programmed to receive sensed pressure data from the sensor 315
and perform analytics to determine the condition of the filter and
generate alerts representative of such condition. A wireless
circuity 325, such as a Bluetooth communication circuit may be used
by the processor 320 to communicate via a wireless network
connection. A battery 330 may be used to power the processor,
sensor, and circuitry. An antenna 335 is also coupled to the
communication circuitry 325 for transmission and reception of
wireless signals.
[0060] FIG. 4 is an illustration of a simulated, graphical user
interface of an application running on a mobile device 400. The
user interface in various embodiments provides an indication of the
condition of a filter being monitored. The application receives
communications from the sensor 300 representative of the condition
of the filter and provides information to a user via the user
interface indicated at 410. The user interface may include a graph
415 or other depiction illustrating filter performance, such as a
line showing a percentage blockage of the filter, a percentage
usage of the filter, and an expected time to replacement of the
filter. The user may be provided with options, such as set 420 and
accept 425. The options may include an option to automatically
order a replacement filter at a time corresponding to a selected
useful life remaining, or immediately upon determination that
filter performance has deteriorated past a selected or determine
threshold. The application may obtain replacement filter part
information from the ID associated with the filter as described
above via RFID or NFC reader, or even scanning a bar code or QR
code on the filter. Alternatively, the ID associated with the
filter may be communicated from the filter sensor to directly or
indirectly to the device running the application via Bluetooth or
other wireless communication protocol.
[0061] There are various methods which may be used to calibrate the
filter sensor once it is installed in furnace system. Tests may be
performed to determine the advantages and disadvantages of each
calibration method.
[0062] Filter Sensor Calibration Method #1:
[0063] 1. Install filter sensor in filter
[0064] 2. Install filter into furnace system
[0065] 3. Start device application
[0066] 4. Push "Calibrate" button to set Differential
Pressure=0
[0067] 5. Start furnace
[0068] 6. Press "Get Data" to take a Differential Pressure
reading
[0069] In some embodiments, the mobile device application may be
used to scan a visible code or obtain information from the filter
using RFID, NFC, or other wireless method to identify the filter.
In some embodiments, the information necessary to identify the
filter may be stored on the sensor and transmitted (directly or
indirectly) to the mobile device. The identification of the filter
may be used to check a table for proper settings to determine
whether or not to notify a user that a filter should be replaced.
If the filter identification is not proper, the app may be designed
not to work with the filter. For example, the application may be
configured to prevent a reset on a sensor that has already
indicated the end of filter life. The application may store or
access the sensor address and filter condition in memory and may
prevent the user from pairing with a sensor that has been removed
from a first filter and coupled to a second.
[0070] Filter Sensor Calibration Method #2:
[0071] 1. Install filter sensor in filter
[0072] 2. Install filter into furnace system
[0073] 3. Start furnace
[0074] 4. Start mobile device application
[0075] 5. Push "Calibrate" button to set Differential
Pressure=0
[0076] 6. Press "Get Data" to take a Differential Pressure
reading
[0077] To check the performance and operation of the pressure
sensing unit, two experiments were completed using the sensing unit
on 1) lab scale hvac system and 2) an actual household furnace. The
sensing unit was first placed in a lab scale HVAC system which has
the ability to vary the blower speed, measure airflow rate, and
measure pressure drop across the filter using a pressure
transducer. With the ability to control the blower speed, this test
was run using a wide range of airflow speeds to provide a range of
sensor responses.
[0078] The sensor was mounted near the center of the filter and
then installed into the filter holder and into the lab scale HVAC
system. FIG. 5A is a table indicating blower speed in feet per
minute, differential pressure sensor readings in millibars, duct
pressure, a calculated pressure, and a letter, A, B, or C
correlating results to a graph as shown in FIG. 5B that illustrates
the calculated pressure. The blower speed was set to achieve a
flowrate equal to 300 fpm (typical test velocity) through the
filter. The test was allowed to run for several minutes to generate
pressure drop data at steady state conditions. The blower speed was
then increased to 400 fpm and 500 fpm to again measure the sensor
responses at these higher airflow velocities. At each of the test
velocities, pressure drop was recorded from the pressure
transducer. The recorded pressure drop was then compared to the
sensor pressure drop to establish a correlation on these
responses.
[0079] The results show a very good correlation between the lab
scale HVAC system dP and the sensor dP (R{circumflex over (
)}2=0.996, see FIG. 6 illustrating a plot comparing the pressures.)
FIGS. 7, 8, and 9 illustrate a further test with HVAC modes
changed, including a fan on and off with both AC on and AC off.
Letters are again used to correlate the test results in the table
in FIG. 7 with a graph in FIG. 9. FIG. 8 is a plot comparing the
pressures in a manner similar to FIG. 6. A significant pressure
difference is noted with the fan and/or AC on. In one embodiment,
improved sensor sampling may result with the use of a filter with a
thru-channel or designed channel that reduces or eliminates
turbulence of air flow. In one embodiment, the sensors may be
placed perpendicular air flow, shielded from direct air flow,
recessed to air flow, set to some other angle than perpendicular
that improves the sampling, set backward, or may have self-cleaning
capabilities.
[0080] FIG. 10 is a block diagram of a device or system 1000 for
sensing obstruction of an air filter according to an example
embodiment. System 1000 includes a single pressure sensor 1010 on a
clean side of a filter 1015. Sensor 1010 may be attached to the
filter 1015 and provides pressure sensor or airflow capability on
the clean side 1020 of the filter 1015 where the suction between
the filter and a fan 1025 creates a pressure differential while the
fan 1025, also corresponding to a furnace system, is running The
pressure and airflow between the filter 1015 and the fan 1025
decreases as the filter becomes obstructed with contaminants as the
filter is aged by use.
[0081] The device may be powered by a coin cell battery. A larger
battery pack could also be used for longer life. Preferably a power
harvester will be used to generate power and recharge the battery
using airflow, vibration, heat differential or other means. Data
may be provided with a frequency of updates of many times a minute.
More frequent updates or sensor samples may be provided in further
embodiments, or may be reduced in rate to conserve battery life
based on an expected life of the battery as compared to the
expected time until the filter becomes significantly obstructed
such that replacement is recommended.
[0082] In some embodiments, the sensor 1010 may include an
accelerometer. The accelerometer sensor reading may be in the form
of units of movement. The pressure sensor is in Pascal Units or
Inches of Water (delta P at 85 lpm of airflow). An airflow sensor
(vane, thermoelectric, bending, vibration) can also act as a
substitute for the accelerometer and/or the pressure sensor in
combination to determine characteristics in airflow and pressure on
at least one of the clean side and the dirty side of the
filter.
[0083] The communication can be to a mobile device 1030 or to a
Wi-Fi router 1035 or other radio device to uplink to a cloud
platform. Radio capability might include but is not limited to:
ZigBee, Zwave, LoRa, Halo(new Wi-Fi), Bluetooth and Bluetooth
BLE.
[0084] Data can be communicated directly to the application on the
mobile device and/or directly to a cloud platform system 1045 via
cellular connection, a Wi-Fi router or a hub. The sensors do not
need to be calibrated before establishing a communication link.
They can be calibrated during or after the initial activation of
the device.
[0085] The device will self-calibrate using intelligent state
management. The device may use an accelerometer or other sensor to
identify when the furnace fan motor is off (reduced vibration or
airflow) and when the fan motor is on (increased vibration or
airflow). The off state will be used to calibrate and compare the
device to the on state over time such as via a machine learning
algorithm 1050.
[0086] FIG. 11 is a block flow diagram illustrating configuration
and use of a mobile device to interact with the filter sensor.
Pairing with the filter sensor may occur, allowing entry of Wi-Fi
credentials via the mobile device. This may allow the filter sensor
to communicate directly with a router within a home of a
customer/user. Updates of data from the filter result in
presentation of a user interface to the user that indicates at
least one of performance (e.g., degraded performance, adequate
performance or optimal performance) and remaining useful filter
life. A notification may also be sent that a filter may be dirty,
obstructed, or otherwise in need of replacement, which may be
displayed on the mobile device for the user to view, or may be
programmed to automatically order a replacement filter or allow the
user to select an option to conveniently order a replacement
filter.
[0087] In some embodiments, specific user needs may be taken into
account in the analytics that determine the need for filter
replacement. A user may enter a profile indicative of specific
medical conditions, such as pollen allergies or other respiratory
conditions where higher than normal air quality may be desired.
Such information may be used by the application to recommend a
different filter, or to change thresholds for generating an
indication of a filter in need of replacement. The ability to adapt
to needs of the user may provide the user with a better overall
experience and ease of use of the smart filter system, relieving
them of having to more closely track the condition of a filter or
save them from using a filter that is not capable of providing a
suitable air quality needed for a better quality of life.
[0088] FIG. 12 is a block diagram of an example system 1400
utilizing two pressure sensors 1410 and 1415, one on each side of
the filter. The use of two pressure sensors provides two
independent pressure sensors to detect the air pressure before the
filter (dirty side as indicated by dirty air arrow 1420) and after
the filter (clean side as indicated by clean air arrow 1425). In
one embodiment, the system includes two pressure sensors 1410,
1415, a circuit and/or logic 1430 that determines pressure
difference as well as a radio (represented by antenna 1435) to
communicate to cellphone 1440 via Bluetooth BLE, Bluetooth or
Wi-Fi, indicated at router 1445.
[0089] A coin cell type battery may be used to provide power to
system 1400. A larger battery pack or other type of power source
could also be used for longer life. Data in the form of updates may
be provided periodically, such as for example, once a minute. More
frequent or less frequent updates or sensor samples could be
provided as desired. Less frequent updates may help conserve
battery life consistent with the length of time the filter is
expected to function within desired parameters. The sensor reading
in one embodiment is in Pascal Units or Inches of Water (delta P at
85 lpm of airflow). The communication can be to a cellphone or to a
Wi-Fi router or other radio device to uplink to a cloud platform.
Data may be communicated to the application directly on the phone
and/or to a cloud platform system via the Wi-Fi router 1445. The
pressure sensors do not need to be calibrated prior to use. In one
embodiment, the pressure sensors may be calibrated during initial
activation of the system.
[0090] In one embodiment, the two pressure sensors may be
calibrated in the factory or in the initial setup relative to each
other as indicated in a block flow diagram 1500 in FIG. 13. The
calibration correction on the device will be represented by the
equation S1=S2+Calibration Correction at 1510 when the airflow is
zero. Calibration may be performed by reading pressures with the
fan off at 1520 and the fan on at 1530. At 1540, the average values
of the reading are determined for sensor 1 and sensor 2, and
provided for calibration correction at 1510.
[0091] Example pressure sensors include: an AdaFruit BME280 I2c or
SPI Temperature Humidity Pressure Sensor, an MPL3115A2-I2C
Barometric Pressure/Altitude/Temperature Sensor (each available
from Adafruit Industries, LLC) and the MPXM2010DT1 and MPXM2010D
(available from NXP USA, Inc.). An exemplary, commercially
available accelerometer is a LIS2DH12TR digital accelerometer from
STMicroelectronics, Geneva, Switzerland. Any one of or both sensors
may be off-the-shelf components that are readily commercially
available.
[0092] In a further example system, one or more sensors monitor
pressure, air flow, air quality, temperature, humidity, distortion
of the filter, airflow characterization and vibration on the clean
and dirty side of the filter (before and after the filter). An
example humidity sensor, an AdaFruit BME280 I2c or SPI Temperature
Humidity Pressure Sensor, is shown in FIG. 14.
[0093] A lab scale furnace experimental system 1700 is indicated in
FIG. 15. A fan 1710 having a controllable fan speed draws air
through simulated ductwork that has a filter 1720 in the center of
the duct work and sensor circuitry 1725 in the form of a circuit
board. The sensor circuitry 1725 receives data from one or more
sensors measuring one or more parameters representative of filter
condition and transmits the resulting information as described
above. The sensor circuitry 1725 may implement an internet of
things (IoT) application protocol to automatically upload and
maintain data on a remote platform for real-time viewing,
retrieval, and analysis.
[0094] FIG. 16 shows an example of data streaming from the
circuitry 1725, which may be wirelessly coupled to a network via an
internet of things (IoT) protocol.
[0095] FIG. 17 is a picture of a filter installed in common home
consumer furnace ductwork that provides a larger test environment.
Sensor packs may be installed before and after the filter. One
sensor pack is visible in the space between the filter and motor
for testing. There is a second sensor pack on the left before the
filter (for testing/calibration). A Wi-Fi signal is able to
penetrate the metal furnace without issue in this configuration
with the plugged-in sensor pack. The sensor pack may for example be
a Raspberry Pi3 with a "sensor hat" that is connected to power to
provide a very rapid sampling rate for high resolution test data.
The data is being uploaded to an IoT Platform. Initial tests
indicated that the sensors are able to pick up the pressure
difference before the filter and after the filter. The sensors may
be run over several days as a "clean" filter to determine the
variance and sensitivity of the sensor over a longer period of
time.
[0096] FIG. 18 is a graph illustrating the difference in pressure
across a filter with the fan first off, then on, then off again.
When the fan is off, the difference in pressure is negligible if
not zero. The top line represents data from the sensor upstream of
the filter and the lower line represents data from the sensor
downstream of the filter. Note that when the furnace is off at the
beginning of the graph and also at the end of the graph, the two
lines rejoin.
[0097] FIG. 19 is a spreadsheet based table indicating information
transmitted and collected during operation of a system including a
smart filter.
[0098] "States" of operation are identified for the furnace at the
point of the individual sensor unit being initiated with a filter
change. These states include:
[0099] Furnace Off--The furnace assumes the pressure level of the
ambient air while having a low level of vibration.
[0100] Furnace On Clean Filter--The clean side sensor establishes a
level of pressure.
[0101] Furnace On Variation 1 . . . n--The furnace establishes
several potential regular "states" as it runs over time. These
states are established during the 2-month phase of the filter in
use.
[0102] Furnace On Dirtying--Levels of obstruction are determined
relative to the Furnace On Variation states established during the
first two months.
[0103] Furnace Filter Needing Changing--Is established when the
furnace filter reaches a predetermined state, such as for example,
an average of 1.5 pascals of pressure less than that of a
previously established state or 3.25 months has been reached during
Furnace On relative to any state.
[0104] The data file from a first Experiment 1 on the full-sized
furnace was reviewed with the following averaged results as
follows.
[0105] Before Filter--Pi Serial Number 43--off calibration Average
986.3636
[0106] After Filter--Pi Serial Number 36--off calibration Average
986.3614
[0107] Before Filter--Pi Serial Number 43--clean running Average
986.2444
[0108] After Filter--Pi Serial Number 36--clean running Average
985.8823
[0109] Before Filter--Pi Serial Number 43--unknown dirty Average
986.0958
[0110] After Filter--Pi Serial Number 36--unknown dirty Average
985.2246
[0111] Before Filter--Pi Serial Number 43--dirty 0.74 Average
986.1727
[0112] After Filter--Pi Serial Number 36--dirty 0.74 Average
985.2684
[0113] Before Filter--Pi Serial Number 43--dirty 1.54 Average
986.3910
[0114] After Filter--Pi Serial Number 36--dirty 1.54 Average
984.1002
[0115] Initial results demonstrate the ability of low cost sensors
being able to establish the pressure differential between the
before filter and after filter sections of the furnace. The results
also suggest the ability of a system to establish states over time
with one or more sensors effectively. The "furnace off" state would
allow for one or more sensors to calibrate relative to atmospheric
pressure changes as well as furnace configuration changes over
time.
[0116] Algorithm Method
[0117] A system including one or more pressure sensors in addition
to accelerometer sensors can establish states of the furnace over
time:
[0118] S0--Filter Installation--Furnace Off
[0119] S1--Filter Clean--Furnace On
[0120] S2 . . . n--Self Characterized States within Month 1-2
[0121] Sr--In Need of Replacement--Characterized by an average
change of 2+ pascals difference from S0 or from pre-filter pressure
sensor while in the on state relative to S0 or 1.5+ pascals as
compared to any of S2 . . . n Self Characterized States.
[0122] Since different type of sensors that sense different
parameters that may be directly representative of filter media
condition may be used in different embodiments, a more generic
algorithm may include similar steps that are not limited to the use
of only pressure sensors. The "in need of replacement" thresholds
may be based on a change in airflow, a change in motor loading,
changes in vibrations, and other parameters sensed by appropriate
sensors as described in further detail below.
[0123] Additional Methodology Detail
[0124] State Value--The value of a state is calculated via a
multistep process. The primary deterministic state is the condition
of the furnace being on or off The second step is a stabilization
period, such as a delay of two minutes after the furnace turning on
or off for airflow, vibration and pressure stabilization. The third
step is to gather data for a period of time (e.g., two minutes).
Outlier data of 2.times. the moving average is removed and the
moving average for the period is established for the after filter
pressure sensor. Vibration (accelerometer data) can be used to
further determine the on/off state of the furnace. Initial
experimentation suggests that a single sensor can be used for this
determination.
[0125] Additional Contributing Factors
[0126] Room air pollution information (particulates and other
contaminates) can be used to improve the accuracy of the need to
change air filtration media.
[0127] Metadata/General Survey Information--Smoking, use of
candles, ownership of pet information can be used to inform the
algorithm to more aggressively determine change.
[0128] General Building Configuration--Windows open/closed,
carpeting as well as other information can be used to inform the
algorithm.
[0129] Outdoor Air Pollution--Information can be gathered from air
quality monitoring sites to determine aggressiveness of
replacement.
[0130] Analytics may be used to filter and provide air quality
advice, furnace status and filter replacement status throughout the
life of the filter. The system may be powered by a coin cell
battery. A larger battery pack could also be used for longer life.
A power harvester may be used to generate power and recharge the
battery using airflow, vibration, heat differential or other means.
Other power sources and storage methods can be used as needed. The
system may provide updates at various time intervals, such as many
times a minute. More frequent updates or sensor samples could be
provided. Frequency of updates may be controlled by air
movement.
[0131] Air pressure may be measured before and after the filter to
be able to determine pressure difference. Multiple sensors may be
used to correct for failure of individual sensors. Filaments and
airflow sensors may be included to provide a map of air turbulence
within the air chambers before and after the filter. The air
turbulence information can be used to determine obstruction or sub
optimized performance of the filter or furnace controls.
[0132] Air quality may also be monitored before filter and after
filter to provide particulate and non-atmospheric gas values to
monitor filter performance and air quality before and after
treatment. Air quality monitors/sensors may also be disposed
outside the HVAC system and within the building or home. Air
temperature in the air stream may also be monitored. Air humidity
in the air stream may also be monitored. Strain sensors may be used
to monitor the distortion of the physical filter shape during the
life of the filter. Strain gauge capability may be woven into the
filaments of the filter.
[0133] Directional (gyroscopic) and non-directional (accelerometer)
measurements may be provided by sensors to understand vibration
which may result in relative strain within the components of the
furnace system. Communication capabilities may be included to
provide information to a mobile device such as a cellphone or to a
Wi-Fi router or other radio device to uplink to a cloud platform.
Radio capability might include but is not limited to: ZigBee,
Zwave, LoRa, Halo (new Wi-Fi), Bluetooth and Bluetooth BLE. Data,
including notifications, can be communicated to an application
directly on the mobile device and/or to a cloud platform system via
the Wi-Fi router. Note that the sensors do not need to be
calibrated beforehand. They can be calibrated in the initial
activation of the device.
[0134] FIG. 20 is a graph indicating readings from a single
downstream side pressure sensor with the furnace or fan off, and
then on, where the filter is known to be dirty and in need of
replacement. Note that the pressure changes by more than 2 pascals,
moving from almost 986.5 pascals when off to less than 984.5
pascals when on. By recording pressure both when the fan is on and
off, the difference may be found by subtraction. Comparison to a
threshold of 2 pascals indicates that the threshold has been
exceeded based on the data shown in FIG. 20.
[0135] The pressure in uncalibrated pascals (low cost sensor) is on
the left (Y-axis) (982-987) over time with the time increments on
the X axis. The sample experiment data shows the off state changing
from a high pressure of 986.5000 to approximately 984.0000 when the
furnace is turned on. The pressure differential is produced by the
difference in ambient air pressure (approximately 986) is
obstructed by the fan operation of the furnace fan behind the
obstructed fan which produces an air pressure reduction to
approximately. 984.
[0136] A single pressure sensor can be used to determine furnace
state (on or off) by the rapid nature of the pressure change.
Atmospheric pressure change occurs more slowly. The on/off periods
can be used to determine the comparator for the determination of
the state Sr (need to change the filter).
[0137] Several different example embodiments have been described
above. FIG. 21 is a block diagram representation of a smart filter
with various options for providing an ID of the filter, sensing the
filter media condition, and optionally sensing air quality. Further
details regarding the options is provided with a discussion of FIG.
22.
[0138] An overall smart filter system view with various options is
now described. FIG. 22 is a block diagram representation of
multiple elements and alternative elements in a smart filter system
2400. System 2400 comprises three major elements, an air filter
2410 that is self-aware when in use, software algorithms 2412 that
collect data from the filter 2410, and a user interface 2414 to
display relevant information on a display, such as a mobile device
display. The mobile device may be a laptop computer, cellular
telephone, tablet, or other device capable of receiving,
processing, and displaying information.
[0139] Self-Aware Filter 2410 may be self-aware by means of a
circuit incorporated into the filter, attached to the filter during
installation, or in a frame the holds the filter. Once the filter
is installed, it can identify that it is a particular brand, type,
or size of filter, and provide digital data about the filter during
operation. In addition, the filter may provide data regarding air
quality of air moving through the system 2400.
[0140] Software algorithms 2412 collect data from one or more
sensors and manipulate the data for future analysis, and store
multiple data strings (from multiple collection sessions) for
future transmission and reporting.
[0141] The user interface 2414 presents the data in a format that
lets the end user readily see filter performance. It may provide
historical data and/or current conditions. It may offer a
prediction of time to filter replacement based on filter condition
and time of use. It can provide data in any format useful to the
consumer including alerts and automatic ordering capabilities. It
may display air quality data at a room, building, facility, or
campus level. Air quality data may be pulled from external air
quality monitoring services, air quality monitoring devices outside
the HVAC system, or one or more sensors in the HVAC system.
[0142] A Filter ID 2416 can be passive 2418 or active 2420. Passive
ID embodiments may include use of a magnetic switch 2422 which
closes when the filter is inserted, or by having a simple socket
2424 built into the filter that activates the circuit when it is
plugged in. Active means 2420 could be accomplished by means of a
passive resonant circuit 2426 attached to an HVAC device which
resonates when the filter and sensor circuit are installed therein.
Other means could be used to detect the filter such as RF ID tags
2428, NFC tags 2430, or by reading a bar code or QR code 2432. In
another embodiment, the Filter ID may be programmed on the sensor
2431 and communicated from the sensor via Bluetooth or other
wireless communication protocol to a mobile device or cloud
platform.
[0143] Media Condition 2434 can be determined by an electronic data
collection circuit and a sensor 2436, and reported by wireless
transmission shown under a communications block 2438. There are a
variety of sensors 2436 that may be used in order to evaluate the
condition of the filter. A physical sensor 2440 can evaluate
eventual bowing of the filter using a strain gauge 2442. Other
sensors that could be used include optical 2444, pressure 2446, air
flow 2448 or vibration 2450. There are a number of different
versions of each type of these sensors. The pressure sensor 2446
may be a differential pressure sensor 2452 or a single pressure
sensor 2454 that may integrate pressure over time or compare
pressure measurements when a fan is on and off
[0144] Optical 2444 media condition sensing may detect fowling 2456
by measuring transmission of light through the media via a
photodetector for example. Airflow 2448 may be indicative of fan
operation, which may be used in conjunction with a pressure
measurement from a single downstream filter to determine the
condition of the filter. In further embodiments, airflow sensors
may be used to measure the change in airflow over time, with
decreased airflow being associated with a deteriorating condition
of the filter media. A threshold corresponding to the decrease in
airflow may be used to determine that the filter should be
replaced. Airflow may be measured by electrical means 2458
including for example vibration sensor 2460, thermoelectric sensor
2462, or bend sensor 2464 (piezoelectric based in one embodiment).
Mechanical means 2466 of sensing may include a vane based sensor
2468 to measure air turbulence, which may represent fan operation
as well as filter media condition, as turbulence may change
responsive to deterioration of filter media condition. Each of
these sensors provide information regarding operation of the fan.
In some embodiments, operation of the fan may be detected by
measuring current flow to the fan to provide an indication of
loading on the fan motor, which may be directly representative of
the condition of the filter media.
[0145] When data from multiple sensors is collected, the data may
be fused in multiple different ways to determine the filter media
condition. For instance, data representative of fan operation may
be used with a single downstream pressure reading in one
embodiment. Vibration information may be combined with pressure in
a further embodiment. Multiple vibration and turbulence
measurements may be used in further embodiments. Many different
sensors, either individually or combined may provide information
from which the condition of the filter media may be calculated in
various embodiments, either from the information of any one or of
the sensors or from information fused from multiple sensors.
[0146] Data that is collected can be communicated at one or more
options under communications 2438. Communications by wireless means
can be accomplished using a variety of wireless protocols including
wireless 2.4 GHz or 5 GHz, Bluetooth or Bluetooth BLE 2470, ZigBee
2472, Zwave 2474, Halo, or other standard or custom protocols
represented at 2476.
[0147] Power 2478 for circuitry, including sensors, can come from a
variety of sources. One option is a battery 2480. Alternately,
energy for operating the circuit can be harvested 2482 from the
environment. Examples could be devices that generate power from air
movement 2484 when the HVAC system is in operation, such as a
turbine 2486 or via vibrations 2488 utilizing an oscillating ribbon
with piezoelectric 2489 or inductive generators 2490. Alternately
power could be generated using the thermoelectric effect 2492, or
power could be supplied externally with an RF transmission signal
2494.
[0148] Air Quality 2496 can be defined in a number of ways
depending on many factors but could include measurement via sensors
2498 of particulate on the clean air side, measuring VOCs,
measurement of particulate in a given room or building, etc.
[0149] Under certain circumstances, the smart filter system may
lack information sufficient to determine media condition based
solely on data from a sensor or multitude of sensors. For instance,
the user may leave the home for a week and yet leave his or her
HVAC system running As another example, the user may move to a
location in the home or facility beyond the reach of the wireless
communication signal. Each circumstance results in potential loss
of data communication between the sensor and the user's mobile
device, but the filter condition will continue to deteriorate.
Depending on the duration of the communication loss, the Media
Condition reported to the user may not accurately reflect status of
a filter media. In these and other situations, it may be possible
to supplement an output of a predictive filter replacement
algorithm for sensor data over the requisite time period.
[0150] In one example, the missing data is supplemented by
estimating replacement status as a function of HVAC fan runtime.
Fan runtime can be estimated using outdoor weather data and can be
adjusted in accordance with parameters relevant to the particular
air filter and/or HVAC system operating conditions, such as
dwelling parameters, HVAC use parameters, user preference
parameters, and filter parameters. The weather data can be obtained
for a particular region, for example, from an online data service.
The weather data can be used to estimate air filter runtime, and
the air filter runtime can be used to estimate the replacement
status of the air filter. Exemplary methods for estimating filter
replacement status as a function of fan runtime are described in
International Publication No. WO 2016/089688 (Fox et al.), which is
incorporated by reference in its entirety herein.
[0151] FIG. 23 illustrates an exemplary sequence for shifting
between sensor data and estimated status in reporting filter
condition. At Step 3000 and "Time 0" a communication link is
established between a Self-Aware Filter and a mobile device or
cloud platform. At step 3100 and "Time 1", the communication
provides substandard or no data from the sensor. Data may be
substandard, for example, if a confidence value assigned to a given
output parameter is not met or exceeded. In Step 3200 and "Time 2",
the time period of substandard or lacking data reaches or exceeds a
Shift Threshold, which may be based on, e.g., the amount of time
between successful communication links or predictive results. Once
the Shift Threshold is exceeded, outdoor weather data for a
geographical region related to the HVAC system is obtained (e.g.,
electronically retrieved from an online data service) in Step 3300.
Outdoor weather data can be collected contemporaneously with data
from the sensor(s), or such collection may be triggered upon
reaching the Shift Threshold. In Step 3400, the replacement status
of the air filter is approximated using the outdoor weather data.
For example, the outdoor weather data is used to estimate air
filter runtime, and the air filter runtime is used to estimate the
replacement status of the air filter. The estimation can be
provided to the user via the user interface, which may or may not
share a sensory experience similar to estimation premised primarily
on sensor data. At Step 3500, the Self-Aware Filter establishes a
communication link with the user's mobile device and/or relevant
output parameters are deemed acceptable at "Time 3". The system may
immediately (or near-immediately) shift back to predicting filter
condition based on data received from the sensor, or may continue
operating based on weather-based estimation until a suitable link
is established for a time period exceeding a Reversion Threshold at
Step 3700.
[0152] An experiment using two sensors, one before a filter and one
after the filter produced the following results during different
states (conditions). Using the pressure difference between the Pi
and P2 sensors (before filter and after filter respectively) as a
determination for filter obstruction measurement is well
understood. Determining if a single sensor before the filter or a
single sensor after the filter can provide enough information to
determine filter obstruction was not previously understood.
[0153] A sample of data during different states of operation for an
experimental furnace provides the following graph data.
[0154] FIG. 24 illustrates multiple pressure measurements
indicative of differential pressure across a filter under varying
conditions over time. A legend indicates various factors with
reference numbers. The different states listed in the legend to the
right (factor(experiment)) are as follows:
[0155] Cleanfilterrunning 2510--this is the furnace with the fan
running with a new clean filter
[0156] Dirty0.74dP 2520--an obstructed filter with the value of
0.74 inches of water
[0157] Dirty1.54dP 2530--an obstructed filter with the value of
1.54 inches of water (more obstructed than 0.74)
[0158] Offcalibration 2540--the furnace is not running and the
pressure is equalized in both chambers to atmospheric pressure
[0159] Unknowndirtyrun 2550--an obstructed filter of unknown
filtration level.
[0160] FIGS. 25, 26, 27, 28, 29, and 30 utilize a similar legend,
with the first two digits of the reference numbers indicative of
the figure number and the last two digits being the same as those
in FIG. 24.
[0161] FIG. 25 illustrates data collected from an accelerometer
sensor measuring vibration in a y-direction in the duct in which
the filter is inserted. FIG. 26 similarly illustrates measurements
of vibration in an x-direction. FIG. 27 similarly illustrates
measurement of vibration in a z-direction. FIG. 28 illustrates
accelerometer results with respect to time in the y-direction. FIG.
29 illustrates accelerometer results with respect to time in the
x-direction. FIG. 30 illustrates accelerometer results with respect
to time in the z-direction.
[0162] Note: Factor(ip) distinguishes TWO DIFFERENT SENSORS.
169.12.46.245 is DOWNSTREAM while 169.12.46.250 is UPSTREAM. The
dirtier the filter, the greater the pressure drop downstream. The
upstream sensors do not identify a significant pressure difference
(right side of graph). These findings suggest that if a single
pressure sensor is used, then the pressure sensor should typically
be placed on the downstream side (after the filter).
[0163] The pressure differential is created by the suction between
the obstructed filter and the fan drawing air. [0164]
P.sub.1=Upstream Sensor Pressure [0165] P.sub.2=Downstream Sensor
Pressure [0166] .DELTA.=P.sub.1-P.sub.2=Pressure Difference between
Upstream Sensor Pressure and Downstream Sensor Pressure T=Time
[0167] A single sensor can work downstream (after the filter) and
the system may be aware of time as well as a state of the furnace
to assist in sensor performance. The state can be determined
through accelerometer information to identify whether or not the
furnace is running, or alternatively the state may be inferred by a
temporal analysis of the pressure measurements. Simply separating
high and low readings and averaging them may clearly identify which
measurements correspond to the state of the furnace. Determining
the pressure when the furnace is off may be useful in determining
the baseline for the current barometric pressure. In one
embodiment, determining the filter condition from a single sensor
includes obtaining time-based pressure data points from the sensor;
calculating a mean difference between obtained adjacent pressure
data points; and estimating filter life based on the identification
of a pressure difference in adjacent points that is greater than a
threshold pressure difference.
[0168] FIG. 31 is a block schematic diagram of a computer system
3200 to implement methods according to example embodiments, such as
implementation of smart filter circuitry and communications and
implementation of a mobile device. All components need not be used
in various embodiments.
[0169] One example computing device in the form of a computer 3200,
may include a processing unit 3202, memory 3203, removable storage
3210, and non-removable storage 3212. Although the example
computing device is illustrated and described as computer 3200, the
computing device may be in different forms in different
embodiments. For example, the computing device may instead be a
smartphone, a tablet, smartwatch, or other computing device
including the same or similar elements as illustrated and described
with regard to FIG. 32. Devices such as smartphones, tablets, and
smartwatches are generally collectively referred to as mobile
devices. Further, although the various data storage elements are
illustrated as part of the computer 3200, the storage may also or
alternatively include cloud-based storage accessible via a network,
such as the Internet.
[0170] Memory 3203 may include volatile memory 3214 and
non-volatile memory 3208. Computer 3200 may include--or have access
to a computing environment that includes--a variety of
computer-readable media, such as volatile memory 3214 and
non-volatile memory 3208, removable storage 3210 and non-removable
storage 3212. Computer storage includes random access memory (RAM),
read only memory (ROM), erasable programmable read-only memory
(EPROM) & electrically erasable programmable read-only memory
(EEPROM), flash memory or other memory technologies, compact disc
read-only memory (CD ROM), Digital Versatile Disks (DVD) or other
optical disk storage, magnetic cassettes, magnetic tape, magnetic
disk storage or other magnetic storage devices capable of storing
computer-readable instructions for execution to perform functions
described herein.
[0171] Computer 3200 may include or have access to a computing
environment that includes input 3206, output 3204, and a
communication connection 3216. Output 3204 may include a display
device, such as a touchscreen, that also may serve as an input
device. The input 3206 may include one or more of a touchscreen,
touchpad, mouse, keyboard, camera, one or more device-specific
buttons, one or more sensors integrated within or coupled via wired
or wireless data connections to the computer 3200, and other input
devices. The computer may operate in a networked environment using
a communication connection to connect to one or more remote
computers, such as database servers, including cloud based servers
and storage. The remote computer may include a personal computer
(PC), server, router, network PC, a peer device or other common
network node, or the like. The communication connection may include
a Local Area Network (LAN), a Wide Area Network (WAN), cellular,
Wi-Fi, Bluetooth, or other networks.
[0172] Computer-readable instructions stored on a computer-readable
storage device are executable by the processing unit 3202 of the
computer 3200. A hard drive, CD-ROM, and RAM are some examples of
articles including a non-transitory computer-readable medium such
as a storage device. The terms computer-readable medium and storage
device do not include carrier waves.
[0173] Although a few embodiments have been described in detail
above, other modifications are possible. For example, the logic
flows depicted in the figures do not require the particular order
shown, or sequential order, to achieve desirable results. Other
steps may be provided, or steps may be eliminated, from the
described flows, and other components may be added to, or removed
from, the described systems. Other embodiments may be within the
scope of the following claims.
Embodiments
[0174] 1. An air filter comprising: filter media; a sensor; and
circuitry coupled to the sensor, the circuitry configured to
receive data from the sensor representative of the condition of the
filter media and wirelessly transmit such data.
[0175] 2. The air filter of embodiment 1 wherein the sensor
comprises a pressure sensor.
[0176] 3. The air filter of embodiment 2 wherein the pressure
sensor is a differential pressure sensor positioned to be exposed
to upstream pressure and downstream pressure with respect to the
filter media while air is moved through the filter media.
[0177] 4. The air filter of embodiment 3 wherein the differential
pressure sensor comprises: a first opening and a second opening,
wherein the second opening comprises a tube configured to extend
from a downstream side of the filter media through the filter media
to an upstream side of the filter media; and a nut adapted to
attach to the tube on the upstream side of the filter media to
retain the differential pressure sensor to the filter media.
[0178] 5. The air filter of any of embodiments 2-4 wherein the
pressure sensor is an absolute pressure sensor supported on a
downstream side of the filter media to measure downstream pressure
while air is moved through the filter media.
[0179] 6. The air filter of embodiment 5 wherein the circuitry is
adapted to determine a pressure difference across the filter media
as a function of the data from the absolute pressure sensor.
[0180] 7. The air filter of embodiment 5 and further comprising a
second sensor to provide second data, wherein the circuitry is
further adapted to combine the second data with the data from the
pressure sensor to determine the pressure difference.
[0181] 8. The air filter of embodiment 7 wherein the second sensor
comprises at least one sensor configured to sense operation of a
fan to move air through the filter material.
[0182] 9. The air filter of embodiment 7 wherein the second sensor
is selected from the group consisting of a strain gage sensor,
vibration sensor, hot wire airflow sensor, strain gage airflow
sensor, and vane airflow sensor.
[0183] 10. The air filter of any of embodiments 1-9 wherein the
sensor comprises one or more sensors selected from the group
consisting of absolute pressure sensor, differential pressure
sensor, strain gage sensor, optical sensor, vibration sensor, hot
wire airflow sensor, strain gage airflow sensor, vane airflow
sensor, and air quality sensor.
[0184] 11. The air filter of any of embodiments 1-10 and further
comprising an electronically readable filter ID, wherein the
circuitry is further adapted to read the filter ID and transmit the
filter ID.
[0185] 12. The air filter of any of embodiments 1-11 wherein the
circuitry is further adapted to generate an alert indicative of a
time to replace the air filter as a function of the sensed
condition of the filter.
[0186] 13. The air filter of any of embodiments 1-12 wherein the
circuitry wirelessly transmits data by at least one communication
protocol selected from the group consisting of Bluetooth, Bluetooth
Low Energy, ZigBee, Zwave, and Wi-Fi.
[0187] 14. A device comprising: a processor; a display coupled to
the processor; and a memory device coupled to the processor and
having a program stored thereon for execution by the processor to
perform operations comprising: wirelessly receiving data from a
sensor representative of the condition of filter media of an air
filter having air flowing therethrough; providing a visual
indication to a user on the display representative of the condition
of the filter media as a function of the received data.
[0188] 15. The device of embodiment 14 wherein the operations
further comprising providing an option to a user of the device to
order a replacement filter.
[0189] 16. The device of any of embodiments 14-15 wherein the
visual indication comprises a graph representative of condition of
the filter media over time, including a remaining period of useful
life of the filter media.
[0190] 17. The device of any of embodiments 14-16 wherein the
visual indication is provided as a function of user profile
information indicative of air quality.
[0191] 18. The device of embodiment 17 wherein the user profile
information is indicative of a medical condition correlated to air
quality.
[0192] 19. A method comprising: wirelessly receiving pressure
information representative of a downstream pressure, the
information received from a sensor associated with an air filter;
processing the pressure information to determine a difference in
pressure between an upstream side of the air filter and the
downstream side of the air filter; and generating an indication of
a condition of the filter responsive to the difference in
pressure.
[0193] 20. The method of embodiment 19 wherein the pressure
information comprises at least one pressure measurement while air
is moving through the air filter and at least one pressure
measurement while air is not moving through the air filter, and
wherein the difference in pressure is determined from such pressure
measurements.
[0194] 21. The method of any of embodiments 19-20 wherein the
pressure information comprises at least one pressure measurement
from the upstream side of the air filter and at least one pressure
measurement from the downstream side of the air filter.
[0195] 22. A method comprising: wirelessly receiving information
representative of a condition of an air filter positioned in a
furnace duct; generating an indication of a condition of the filter
responsive to the received information; and wirelessly transmitting
data representative of the indication of the condition of the
filter to a device for display of the indication to a user.
[0196] 23. A method comprising: sensing a condition of air filter
media; and wirelessly transmitting information representative of
the condition of the air filter media such that the information is
receivable by an end user.
[0197] 24. The air filter of any of embodiments 1-13 and further
comprising means for coupling the sensor to the filter media in a
manner permitting removal and reuse of the sensor with replacement
filter media.
[0198] 25. The air filter of any of embodiments 1-13 and further
comprising: a frame to hold the filter media; and means for
coupling the sensor to the frame.
[0199] 26. The air filter of embodiment 25 wherein the filter media
is replaceable in the frame.
[0200] 27. The device of any of embodiments 14-18 wherein the
operations further comprise: obtaining information from the filter;
and using the information to enable or disable providing the visual
indication to the user.
[0201] 28. The device of any of embodiments 14-18 and 27 wherein
the operations further comprise: obtaining information from the
filter; and wherein providing a visual indication to a user on the
display representative of the condition of the filter media as a
function of the received data is a function of a threshold set
based on the obtained information.
[0202] 29. The device or method of any of the previous embodiments,
wherein the circuitry wirelessly transmits data by at least one
communication protocol selected from the group consisting of
Bluetooth, Bluetooth Low Energy, ZigBee, Zwave, and Wi-Fi.
[0203] 30. The device or method of embodiment 29, wherein the
circuitry transmits data to a mobile device, and wherein the mobile
device, via one or more processors, is adapted to generate an alert
indicative of a time to replace the air filter as a function of the
sensed condition of the filter.
[0204] 31. The device of method of any of the previous embodiments,
and wherein the sensor is releasably coupled to the filter
media.
[0205] The following statements are potential claims that may be
converted to claims in a future application. No modification of the
following statements should be allowed to affect the interpretation
of claims which may be drafted when this provisional application is
converted into a regular utility application.
* * * * *