U.S. patent application number 11/408770 was filed with the patent office on 2007-11-08 for machine and operating environment diagnostics, detection and profiling using sound.
Invention is credited to Douglas George Heintzman, Jiri Navratil, Jason William Pelecanos, Ganesh N. Ramaswamy.
Application Number | 20070256499 11/408770 |
Document ID | / |
Family ID | 38660012 |
Filed Date | 2007-11-08 |
United States Patent
Application |
20070256499 |
Kind Code |
A1 |
Pelecanos; Jason William ;
et al. |
November 8, 2007 |
Machine and operating environment diagnostics, detection and
profiling using sound
Abstract
A method, system and program storage device are provided for
machine diagnostics, detection and profiling using pressure waves,
the method including profiling known sources, acquiring pressure
wave data, analyzing the acquired pressure wave data, and detecting
if the analyzed pressure wave data matches a profiled known source;
the system including a processor, a pressure wave transducer in
signal communication with the processor, a pressure wave analysis
unit in signal communication with the processor, and a source or
threat detection unit in signal communication with the processor;
and the program storage device including program steps for
profiling known sources, acquiring pressure wave data, analyzing
the acquired pressure wave data, and detecting if the analyzed
pressure wave data matches a profiled known source.
Inventors: |
Pelecanos; Jason William;
(Ossining, NY) ; Heintzman; Douglas George;
(Pleasantville, NY) ; Navratil; Jiri; (White
Plains, NY) ; Ramaswamy; Ganesh N.; (Mohegan Lake,
NY) |
Correspondence
Address: |
F. CHAU & ASSOCIATES, LLC
130 WOODBURY ROAD
WOODBURY
NY
11797
US
|
Family ID: |
38660012 |
Appl. No.: |
11/408770 |
Filed: |
April 21, 2006 |
Current U.S.
Class: |
73/579 |
Current CPC
Class: |
G01H 1/00 20130101 |
Class at
Publication: |
073/579 |
International
Class: |
G01H 13/00 20060101
G01H013/00 |
Claims
1. A method for source profiling using pressure waves, the method
comprising: profiling known pressure wave sources; acquiring
pressure wave data; analyzing the acquired pressure wave data; and
detecting a source if the analyzed pressure wave data matches a
profiled known source.
2. A method as defined in claim 1 wherein the detected source is
indicative of a safety threat.
3. A method as defined in claim 1 wherein the detected source is
indicative of at least one of a machine or its environment, the
method further comprising monitoring operating conditions or
measuring properties of the machine or its environment.
4. A method as defined in claim 1 wherein the known pressure wave
sources are profiled using frequency, time or cepstral domain
characteristics.
5. A method as defined in claim 1 wherein the known pressure wave
source profiles are modeled or measured for potential or actual
sources, respectively.
6. A method as defined in claim 1 wherein the pressure wave data is
acquired from at least one of an onboard pressure wave sensor or a
remote pressure wave sensor.
7. A method as defined in claim 1 wherein the pressure wave data is
acquired from a microphone.
8. A method as defined in claim 1 wherein the pressure wave data is
acquired from at least one of an infrasonic or ultrasonic
sensor.
9. A method as defined in claim 1 wherein analyzing the acquired
pressure wave data comprises performing a spectral, periodogram or
autocorrelation analysis on the data.
10. A method as defined in claim 1 wherein detecting a source
comprises template-matching a time or frequency domain
representation of a known pressure wave source with a time or
frequency domain representation of the acquired pressure wave
data.
11. A method as defined in claim 1 wherein detecting a source
comprises detecting multiple sources.
12. A method as defined in claim 1, further comprising indicating a
detected source to an operator.
13. A method as defined in claim 1, further comprising transmitting
a signal indicative of a detected source to a remote location.
14. A method as defined in claim 1 wherein the medium of the
pressure waves is in plasma, gaseous (air), liquid, or solid
form.
15. A method as defined in claim 1 wherein the acquired pressure
wave data is indicative of a sound that a machine component makes
during operation.
16. A method as defined in claim 1, further comprising at least one
of: profiling the acquired data and relaying it back to at least
one of a logging system, a centralized or distributed server, or a
database; or using a detected source or machine/environment audio
profile for traffic enforcement or control or the generation of
statistics.
17. A method as defined in claim 1 wherein: the pressure wave
sensor is used for gathering audible, ultrasonic and/or infrasonic
data; the pressure sensor comprises a single sensor, multiple
sensors arranged in arrays, or at least one sensor in sound dish
form; the acquired data is indicative of the sound of a machine
interacting with its operating environment; the acquired data is
indicative of sounds from the environment other than from a machine
itself, the method further comprising using detected sources to
improve the efficiency or safety of operation of the machine or to
alert its user or for determining sound event statistics; the
pressure wave sensor is placed on a machine itself for on-board
detection and profiling, or remotely for recognizing events at a
distance from the sound source; analyzing the acquired pressure
wave data uses any sound signal processing techniques or
statistical or discriminative methods to obtain information
relating to an acquired sound; the profiled sources are indicative
of sounds from many types of machines, including vehicles that
operate on land, air, sea or in space; the profiled sources are
indicative of sounds from many types of machines, including
machines used in the process of manufacturing such as assembly line
machines, home appliances or workshop tools; the acquired data is
indicative of machine exhaust systems, engine or motor operation,
tire, wheel or landing gear performance or integrity; a detected
source is indicative of a fault in the structural integrity of a
machine; a profiled known source is indicative of the repeating or
cyclical nature of a sound; detection of a source matching a
repeating or cyclical profile is responsive to an autocorrelation,
periodogram, cepstral and/or spectral analysis of the pressure wave
signal; the acquired data is indicative of a running engine, and a
profiled source is responsive to a time delay between each piston
firing in the engine, the number of pistons firing per revolution
in an engine, the number of pistons present in an engine, or a
defective valve or spark plug attributed to the absence or
aberration of a mode or characteristic of the acquired signal; the
detected source is responsive to a sound made by at least one of a
leading or a current vehicle encountering an environmental defect
in the path of travel; or the detected source is responsive to a
sound made by a vehicular or machine suspension when a tire or
support impacts against a pothole, defect or otherwise unusual
material in the path of travel or material feed.
18. A system for source profiling using pressure waves, the system
comprising: a processor; a pressure wave transducer in signal
communication with the processor; a pressure wave analysis unit in
signal communication with the processor; and a source or threat
detection unit in signal communication with the processor.
19. A system as defined in claim 18 wherein the pressure wave
transducer comprises at least one microphone, infrasonic or
ultrasonic sensor mounted on-board or remotely.
20. A program storage device readable by machine, tangibly
embodying a program of instructions executable by the machine to
perform program steps for machine diagnostics, detection and
profiling using pressure waves, the program steps comprising:
profiling known sources; acquiring pressure wave data; analyzing
the acquired pressure wave data; and detecting if the analyzed
pressure wave data matches a profiled known source.
Description
BACKGROUND
[0001] The present disclosure generally relates to pressure wave
detection, and more particularly relates to profiling or diagnosis
of machines or their environments using pressure waves. Pressure
waves are transmitted through air, and include sound waves in the
audible frequency range, as well as infrasound and ultrasound
waves.
[0002] The safety of people and transportation systems is of
paramount importance. Many people rely on automobile transportation
as a primary means of transport. The New York State Department of
Motor Vehicles reported, in statewide statistics for the calendar
year 2003, that vehicle defects contributed to at least 5% of all
automobile accidents. In addition, there were approximately 600
accidents reported as being attributed to tire failure and 1200
related to brake failure. Operator error and environmental
conditions also affect the safety of travel. Consequently, there is
a need to improve the safety of vehicles traveling on public
roadways.
[0003] Safety imperatives are not confined to road based
transportation. For example, infrasound data might be used to warn
airplane pilots of currently undetectable and dangerous clear-air
turbulence. Such technology may be useful for transportation via
automobile, airplane, train and subway, where operator error,
mechanical defects and/or environmental factors, if undetected, may
contribute to hazardous conditions.
[0004] Safety initiatives introduced by vehicle manufacturers,
public safety agencies and insurance companies generally rely on a
multi-pronged approach. From a manufacturer's perspective, safety
is addressed through crash avoidance mechanisms and damage
mitigation. From the public safety viewpoint, controls are
introduced through education campaigns, traffic monitoring and
enforcement. That is, traffic authorities have mechanisms to
statistically address road safety through educating and fining
drivers perceived to be careless, and performing vehicle
inspections or roadworthiness tests to exclude relatively dangerous
equipment. Through increased insurance rates, insurance companies
have another way to penalize the vehicle operators and/or owners in
the years subsequent to a public safety violation. A remaining
challenge is to provide effective technologies to support increased
travel safety in a more direct, proactive and timely manner.
[0005] The various needs of vehicle manufacturers, owners,
operators, passengers and pedestrians, as well as those of the
traffic regulatory authorities, may be addressed by providing early
vehicular hazard detection technologies and environmental hazard
detection systems. In a typical case, an operator would not be
aware of an impending vehicle failure or environmental hazard until
it occurred. Through early detection, many of these impending
equipment failures and/or environmental hazards may be detected,
and the proximate hazardous situations may be averted.
[0006] There are a number of discrete accident prevention
technologies that focus on safety from different viewpoints. Such
examples of in-vehicle accident prevention technologies include
automatic braking systems, networked engine diagnostics,
all-wheel-drive, stability controls, tire pressure monitoring
systems, and tailgating prevention mechanisms. In addition to
safety, these and other technologies may have application to the
maintenance, diagnosis and optimal performance of machines and
their environments. These technologies may significantly boost the
safety margins of under-maintained vehicles and/or relatively
unskilled operators closer to the levels of well-maintained
vehicles and/or highly skilled operators.
[0007] Unfortunately, each of these technologies is separate and
distinct. In addition, each is burdened with its own associated
additive costs and drawbacks. There are also technologies that can
alert the user to impending risks by selectively playing amplified
audio events according to their importance or location. Thus, it is
desirable to address safety, maintenance, diagnosis and/or
performance optimization of machines and their environments. What
is needed is an improved method for detecting a broader range of
disparate safety threats, at least some of which were heretofore
difficult or impossible for even skilled operators to sense or
recognize.
SUMMARY
[0008] These and other drawbacks and disadvantages of the prior art
are addressed by a system and method for machine and operating
environment diagnostics, detection and profiling using sound.
[0009] An exemplary method is provided for machine diagnostics,
detection and profiling using pressure waves. The exemplary method
includes profiling known sources, acquiring pressure wave data,
analyzing the acquired pressure wave data, and detecting if the
analyzed pressure wave data matches a profiled known source.
[0010] An exemplary system is provided for machine diagnostics,
detection and profiling using pressure waves. The exemplary system
includes a processor, a pressure wave transducer in signal
communication with the processor, a pressure wave analysis unit in
signal communication with the processor, and a threat detection
unit in signal communication with the processor.
[0011] An exemplary program storage device is provided for machine
diagnostics, detection and profiling using pressure waves. The
exemplary program storage device includes program steps for
profiling known sources, acquiring pressure wave data, analyzing
the acquired pressure wave data, and detecting if the analyzed
pressure wave data matches a profiled known source.
[0012] These and other aspects, features and advantages of the
present disclosure will become apparent from the following
description of exemplary embodiments, which is to be read in
connection with the accompanying drawings.
BRIEF DESCRIPTION OF THE DRAWINGS
[0013] The present disclosure teaches machine diagnostics,
detection and profiling using sound in accordance with the
following exemplary figures, in which:
[0014] FIG. 1 shows a schematic diagram of a system for machine
diagnostics, detection and profiling using sound in accordance with
an illustrative embodiment of the present disclosure;
[0015] FIG. 2 shows a flow diagram of a method for machine
diagnostics, detection and profiling using sound in accordance with
an illustrative embodiment of the present disclosure;
[0016] FIG. 3 shows a schematic diagram of exemplary configurations
for sound based profiling in accordance with illustrative
embodiments of the present disclosure; and
[0017] FIG. 4 shows a graphical diagram of an audio-based
autocorrelation analysis for an automobile drive-by in accordance
with an illustrative embodiment of the present disclosure.
DETAILED DESCRIPTION OF PREFERRED EMBODIMENTS
[0018] Pressure wave or sound technology can be used to address
existing shortcomings of road and vehicle safety, and can provide
safety mechanisms unlike any other current technology. This
technology can be used to diagnose technical problems with the
vehicle or machine, identify hazardous conditions, monitor road
quality or regulate the roadworthiness of vehicles either locally
on the machine itself, or remotely from a distant location.
Unfortunately, there are few known devices that detect the hazards
of the environment that the vehicle may be operating in for the
purpose of alerting the driver. Pressure wave or sound technology
has an essential role that can address this void.
[0019] Exemplary embodiments of the present disclosure utilize
sound waves generated by the vehicle or machine, the environment,
or the interaction between the two, to profile, detect or diagnose
vehicular and/or environmental hazards or characteristics. In one
embodiment, driver and passenger safety is improved by
automatically detecting, via sound waves, mechanical or other
defects while the vehicle or machine is in operation.
[0020] Conventional solutions rely on a human operator to determine
a problem with the vehicle or machine, typically using the human
senses. In many circumstances, the human operator would not be
aware that there is a defect until a catastrophic failure occurs.
In addition, safety officials can use such a device to detect
unsafe machines from a distance and have the problem repaired or
enable the machine owner to be informed. An automatic solution that
may be activated onboard the machine itself or remotely to detect
sound events is a highly desired solution. This solution will
likely reduce machine repair costs because of early detection, and
ultimately increase human safety.
[0021] An exemplary method uses microphones and corresponding
signal processing techniques to immediately identify sounds of
interest while the machine is operation. These sounds of interest
may be noises attributed to a car traveling along the highway with
a flat pneumatic tire, or a tire with a bulge or cut in it. The
method can be applied to any machine while in normal operation. The
sensors can be onboard the machine for the purpose of in-car
diagnostics, for example, or operated a distance from the sound
source as in typical police radar and safety enforcement scenarios.
The technology enables automobiles, as well as other types of
vehicles and crafts, to automatically determine failures that would
not be readily detectable otherwise using direct measurement. The
system can be easily tailored to provide an early warning to
hazardous events in an on-device manner, or in hostile and
otherwise inaccessible environments through remote sound detection,
diagnostics and profiling.
[0022] An exemplary device is capable of detecting numerous types
of hazardous conditions and other profile information. These
conditions are detected and profiled by analyzing the sound waves
that may be attributed to the hazardous situation. The device
operates as follows; (i) an audio or infra/ultra sonic microphone
measures the airwaves or mechanical vibrations (a sound dish or
microphone array also achieves this purpose), (ii) the signal is
amplified, (iii) pertinent features are extracted and (iv) the
signal is classified or profiled.
[0023] The sound based device can be operated in four distinct
configurations. The first mode is when the system attempts to
detect problems with (or determine audio profile statistics for)
the machine that is in operation through a sound based analysis
(using audio, infra- and/or ultrasound wave information). The
second configuration is to detect problems with (or determine audio
profile information for) the environment in which the system is
running. For each of these configurations, the sound sensing system
may be operated locally on the machine (or in the particular
environment) or remotely from a distance to the noise source of
interest.
[0024] As shown in FIG. 1, a system for machine diagnostics,
detection and profiling using sound, according to an illustrative
embodiment of the present disclosure, is indicated generally by the
reference numeral 100. The system 100 includes at least one
processor or central processing unit (CPU) 102 in signal
communication with a system bus 104. A read only memory (ROM) 106,
a random access memory (RAM) 108, a display adapter 110, an I/O
adapter 112, a user interface adapter 114 and a communications
adapter 128 are also in signal communication with the system bus
104. A display unit 116 is in signal communication with the system
bus 104 via the display adapter 110. A disk storage unit 118, such
as, for example, a magnetic or optical disk storage unit is in
signal communication with the system bus 104 via the I/O adapter
112. A mouse 120, a keyboard 122, and an eye tracking device 124
are in signal communication with the system bus 104 via the user
interface adapter 114.
[0025] A pressure wave transducer or microphone 132 is in signal
communication with an input adapter 130, which, in turn, is in
signal communication with the system bus 104 and the CPU 102. A
pressure wave analysis unit 180 and a pressure wave source
detection, audio profiler, or safety threat detection unit 190 are
also included in the system 100 and in signal communication with
the CPU 102 and the system bus 104. While the pressure wave
analysis unit 180 and the threat detection unit 190 are illustrated
as coupled to at least one processor or CPU 102, these components
are preferably embodied in computer program code stored in at least
one of the memories 106, 108 and 118, wherein the computer program
code is executed by the CPU 102.
[0026] Turning to FIG. 2, a method for machine diagnostics,
detection and profiling using sound is indicated generally by the
reference numeral 200. The method 200 includes a start block 210,
which passes control to a function block 212. The function block
212 profiles known types of sources and/or safety threats, and
passes control to an input block 214. The input block 214, in turn,
receives pressure wave data, such as from a microphone, and passes
control to a function block 216.
[0027] The function block 216 analyzes the acquired wave data, such
as by performing a fast-Fourier transform analysis, an
autocorrelation analysis, a periodogram analysis, or by using
various feature extraction and pattern classification techniques.
The function block 216 may perform profile analysis for matching as
well as estimation of machine operating parameters, such as
estimating the RPM of an engine, for example. The function block
216 passes control to a decision block 218. The decision block 218,
in turn, determines whether the analyzed wave data matches the
profiles for any known sources and/or safety threats, and if so,
passes control to a function block 220 to detect the source or
safety threat. The function block 220 may pass control to an end
block 222. If no source or safety threat matches are found, the
decision block 218 passes control back to the input block 214.
[0028] Turning now to FIG. 3, configurations of sound based
profiling are indicated generally by the reference numeral 300.
Each configuration demonstrates a car-based application using sound
detection and profiling. Acquisition of the sounds may involve the
use of microphones, infrasonic, ultrasonic and/or long distance
sound sensors.
[0029] In an exemplary local system profiling configuration, a car
310 is equipped with four corner or tire sound sensors 312, at
least one engine sound sensor 314 and at least one exhaust sound
sensor 316. Here, the sound sensors are designed to provide
information to the driver regarding detected problems relating to
at least the car engine, exhaust or tires. For instance, the driver
of the car may be notified when an object such as a nail is caught
in the tire, the tire has a cut, or that the brakes at that corner
are worn. Sound sensors near the engine and exhaust would provide
information regarding abnormal operation or condition of the
vehicle engine. For example, sensors near the engine and exhaust
would enable the system to detect if a particular piston in an
engine is not firing properly, or if there is insufficient oil in
the engine to lubricate the moving components. This sensing system
provides the mechanism to forward timely information to the user
regarding the status of their vehicle. This will save the user
money and will avoid potentially hazardous situations for the
driver and accompanying passengers.
[0030] In an exemplary local environment profiling configuration, a
car 320 has sound sensors 322 attached onboard the car for the
purpose of profiling the quality of the roads, such as a detecting
a hole 324. This information may be relayed back to a base station
to govern how the roads are maintained. This application can also
be extended to trains for example. The sound sensors may be
incorporated to measure the quality of the individual rails and
preemptively identify rails that will need replacement.
[0031] In an exemplary remote system profiling configuration, a car
330 might have a defective tire 332, which can be detected with a
remote sound sensor 334. For cars that do not have the onboard
sound based sensors installed, public safety personnel can use
remote sound based sensors to detect vehicles or conditions that
represent a safety risk. These sound measurements may be taken
while a vehicle is in motion. Cars with inefficient engines, which
can cause safety hazards by failing to accelerate or maintain
adequate speed, or those with cuts or bulges in their tires or an
unbalanced wheel, may be detected using this approach. In addition,
detecting and correcting inefficient car engines may reduce the
environmental impacts and associated detrimental health effects on
humans that have been attributed to the excessive emissions of
poorly maintained vehicles.
[0032] In an exemplary remote environment profiling configuration,
a detection system on a following car 340 may detect the sounds of
a leading car 342 experiencing emergency braking by means of a
sound sensor 344 mounted near the front of the following car 340.
This scenario enables cars and other vehicles to detect sounds that
may indicate a hazardous condition external to the car itself. This
dangerous condition may relate to the sound of a car threshold
braking, or one skidding its tires, or the sound of an ambulance
siren on an emergency run. The appropriate sound may be detected so
that the better informed driver can take the corresponding
precautions.
[0033] As shown in FIG. 4, an audio-based autocorrelation analysis
of an exemplary car drive-by is indicated generally by the
reference numeral 400. Here, the number of pistons firing or
combustions per second can be identified for internal combustion
engines. As an example of the strength of audio profiling of cars,
the analysis 400 shows the autocorrelation function of an audio
sample of a car drive by, where the spacing between each peak
relates to the delay between each spark plug firing. Assuming that
each spark plug fires once per engine revolution, as in a 2-cycle
engine, the number of revolutions can be acoustically determined.
That is, for a 2-cycle, 4-cylinder system, the fourth peak relates
to 2000 rpm. A determination of 2-cycle versus 4-cycle engines can
also be made using the characteristic sounds produced by each, and
the system will work equally well for reciprocating pistons or
rotary pistons.
[0034] Such information can be used to detect if one piston in an
engine is not firing properly, and this can be achieved while the
vehicle is in motion as opposed to being measured only in a
mechanic's workshop. This provides the opportunity for on-the-fly
vehicle diagnostics and safety. Other periodic information relating
to tire or wheel alignment noises can also be determined using a
similar analysis. This information can also be used as part of a
more comprehensive traffic statistics measurement solution.
[0035] An exemplary method is provided herein for machine
diagnostics, detection and profiling using pressure waves. The
exemplary method includes profiling known sources and/or safety
threats, acquiring pressure wave data, analyzing the acquired
pressure wave data, and detecting a source or safety threat if the
analyzed pressure wave data matches a profiled known source or
safety threat.
[0036] A corresponding exemplary system is provided herein for
machine diagnostics, detection and profiling using pressure waves.
The exemplary system includes a processor, a pressure wave
transducer in signal communication with the processor, a pressure
wave analysis unit in signal communication with the processor, and
a threat detection unit in signal communication with the
processor.
[0037] In addition, an exemplary program storage device is provided
herein for machine diagnostics, detection and profiling using
pressure waves. The exemplary program storage device includes
program steps for profiling known sources and/or safety threats,
acquiring pressure wave data, analyzing the acquired pressure wave
data, and detecting a source or safety threat if the analyzed
pressure wave data matches a profiled known source or safety
threat.
[0038] Thus, exemplary embodiments provide a method of profiling,
detecting and diagnosing machine components based on the sound that
the part makes during operation. The sound sensors used for
gathering the information may be audible, ultrasonic or infrasonic
types, arranged singly, in arrays, or in sound dish form. In
environment profiling configurations, the environment in which a
machine operates may be analyzed. Sounds from the environment,
other than the normal sounds of the machine itself, may be used to
improve the efficiency or safety of operation of the machine or to
alert its user.
[0039] The sound sensors may be placed on the machine itself for
onboard detection and profiling, or remotely for recognizing events
at a distance from the sound source. As will be recognized by those
of ordinary skill in the pertinent art, any audio signal processing
techniques or statistical or discriminative methods may be adapted
to obtain information relating to the sound. Sound information may
be used in the form of a profile, and be relayed with or without a
communications channel back to a logging system, a centralized or
distributed server and/or database. The technology may be used for
traffic enforcement and control scenarios.
[0040] In alternate embodiments, the sounds from many types of
machines may be analyzed. This includes but is not limited to all
vehicles that operate on land, air, sea and in space, such as
bicycles, motorbikes, motor vehicles, trucks, steamrollers,
trailers, vans, sport utility vehicles, boats, ships, trains,
planes, jets, tanks, rockets, shuttles, and horse-drawn buggies.
Applications may also include machines used in the process of
manufacturing, such as assembly line machines, home appliances and
workshop tools. Machine exhaust systems, engine operation,
tire/wheel/landing gear performance and integrity may be monitored.
Structural stability of machines may also be monitored through the
use of sound.
[0041] The environment in which a machine operates may be monitored
by recording and analyzing, where the environment includes, but is
not limited to, the sound from other traffic or machines, and the
roadways and airways. The profile of the sounds may utilize, but is
not limited to, the repeating or cyclic nature of sounds. Cyclical
sound applications may refer to a rotating tire with a defect or
cut located in the tread. The sound of the anomaly in the tire
against the road as the vehicle travels will be of a repetitive
nature. Detection of such a repeating sound may be achieved by, but
is not limited to, an autocorrelation analysis of the sound
signal.
[0042] The sound information from an engine may be used to
determine profile information including, but not limited to, the
number of pistons firing per second in an engine, the number of
pistons in an engine, a defective valve or spark plug attributed to
the absence or attributes of a signal, and the like. Defects in
roadways may be detected through the use of the sound made from a
tire impact against the pothole or defect in the road. Defects in
vehicles and machine suspensions may also be detected through the
use of the sound made when a tire impacts against a pothole, defect
or otherwise special material in the road.
[0043] Preferred embodiments may also be applied to detecting
defects in train tracks or wheels, and to detecting defects on
airplane runways and airplane landing gear. Further, embodiments
may relate to any or all possible machine and environmental sound
examples corresponding to land, sea, air and space travel. In
addition, other embodiments may be applied to detecting faults and
profiling audio from manufacturing machines, workshop tools and
home appliances.
[0044] It is to be understood that the teachings of the present
disclosure may be implemented in various forms of hardware,
software, firmware, special purpose processors, or combinations
thereof. Most preferably, the teachings of the present disclosure
are implemented as a combination of hardware and software.
[0045] Moreover, the software is preferably implemented as an
application program tangibly embodied on a program storage unit.
The application program may be uploaded to, and executed by, a
machine comprising any suitable architecture. Preferably, the
machine is implemented on a computer platform having hardware such
as one or more central processing units (CPU), a random access
memory (RAM), and input/output (I/O) interfaces.
[0046] The computer platform may also include an operating system
and microinstruction code. The various processes and functions
described herein may be either part of the microinstruction code or
part of the application program, or any combination thereof, which
may be executed by a CPU. In addition, various other peripheral
units may be connected to the computer platform such as an
additional data storage unit and a printing unit.
[0047] It is to be further understood that, because some of the
constituent system components and methods depicted in the
accompanying drawings are preferably implemented in software, the
actual connections between the system components or the process
function blocks may differ depending upon the manner in which the
present disclosure is programmed. Given the teachings herein, one
of ordinary skill in the pertinent art will be able to contemplate
these and similar implementations or configurations of the present
disclosure.
[0048] Thus, the present disclosure sets forth an improved method
for detecting a broader range of disparate sources and/or safety
threats than was previously available. Some of the newly detectable
sources or safety threats, particularly when applied in the context
of transportation machines, were heretofore difficult or impossible
for even skilled operators to sense or recognize.
[0049] Although the illustrative embodiments have been described
herein with reference to the accompanying drawings, it is to be
understood that the present disclosure is not limited to those
precise embodiments, and that various changes and modifications may
be effected therein by one of ordinary skill in the pertinent art
without departing from the scope or spirit of the present
disclosure.
[0050] For example, the exemplary method for analyzing pressure
waves may utilize template-matching, modal analysis, frequency
domain and/or time domain analysis alone or in combination with
existing vehicular or machine inputs. In addition, any type of
pressure wave transducer may be substituted for the exemplary
pressure wave transducers disclosed herein. Although the exemplary
embodiments are generally directed towards pressure waves detected
in air, it shall be recognized that pressure waves may propagate
through other media, such as water and solids, in combination with
or in addition to air. All such changes and modifications are
intended to be included within the scope of the present disclosure
as set forth in the appended claims.
* * * * *