# US 11,307,565 B2 · Method and system of a noise pattern data marketplace for motors

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- Number: US 11,307,565 B2
- Document ID: US11307565B2
- Status: Granted
- Kind: B2
- Application number: 16/230,385
- Filed: 2018-12-21
- Published: 2019-05-16
- Granted: 2022-04-19
- Earliest claimed: 2016-05-09
- Assignees: Strong Force IOT Portfolio 2016, LLC
- Applicants: Strong Force IoT Portfolio 2016, LLC
- Inventors: Charles Howard Cella; Gerald William Duffy, Jr.; Jeffrey P. McGuckin; Mehul Desai
- Web page: https://patentgrep.com/patent/US11307565B2

## CPC

- G05B 19/4183: {characterised by data acquisition, e.g. workpiece identification}
- B62D 15/0215: {by measuring on the steering column}
- G01M 13/028: Acoustic or vibration analysis
- G01M 13/04: Bearings
- G01M 13/045: Acoustic or vibration analysis
- G05B 13/028: {using expert systems only}
- G05B 19/4184: {characterised by fault tolerance, reliability of production system}
- G05B 19/41845: {characterised by system universality, reconfigurability, modularity}
- G05B 19/4185: {characterised by the network communication}
- G05B 19/41865: {characterised by job scheduling, process planning, material flow}
- G05B 19/41875: {characterised by quality surveillance of production}
- G05B 23/0221: {Preprocessing measurements, e.g. data collection rate adjustment; Standardization of measurements; Time series or signal analysis, e.g. frequency analysis or wavelets; Trustworthiness of measurements; Indexes therefor; Measurements using easily measured parameters to estimate parameters difficult to measure; Virtual sensor creation; De-noising; Sensor fusion; Unconventional preprocessing inherently present in specific fault detection methods like PCA-based methods}
- G05B 23/0229: {knowledge based, e.g. expert systems; genetic algorithms}
- G05B 23/024: {Quantitative history assessment, e.g. mathematical relationships between available data; Functions therefor; Principal component analysis [PCA]; Partial least square [PLS]; Statistical classifiers, e.g. Bayesian networks, linear regression or correlation analysis; Neural networks}
- G05B 23/0264: {Control of logging system, e.g. decision on which data to store; time-stamping measurements}
- G05B 23/0283: {Predictive maintenance, e.g. involving the monitoring of a system and, based on the monitoring results, taking decisions on the maintenance schedule of the monitored system; Estimating remaining useful life [RUL] (preventive maintenance, i.e. planning maintenance according to the available resources without monitoring the system G06Q10/06)}
- G05B 23/0286: {Modifications to the monitored process, e.g. stopping operation or adapting control}
- G05B 23/0289: {Reconfiguration to prevent failure, e.g. usually as a reaction to incipient failure detection}
- G05B 23/0291: {Switching into safety or degraded mode, e.g. protection and supervision after failure}
- G05B 23/0294: {Optimizing process, e.g. process efficiency, product quality}
- G05B 23/0297: {Reconfiguration of monitoring system, e.g. use of virtual sensors; change monitoring method as a response to monitoring results}
- G06F 18/2178: {based on feedback of a supervisor}
- G06N 3/006: based on simulated virtual individual or collective life forms, e.g. social simulations or particle swarm optimisation [PSO]
- G06N 3/02: Neural networks
- G06N 3/044: Recurrent networks, e.g. Hopfield networks
- G06N 3/045: Combinations of networks
- G06N 3/047: Probabilistic or stochastic networks
- G06N 3/0499: Feedforward networks
- G06N 3/084: Backpropagation, e.g. using gradient descent
- G06N 3/088: Non-supervised learning, e.g. competitive learning
- G06N 3/09: Supervised learning
- G06N 5/046: Forward inferencing; Production systems
- G06N 7/01: Probabilistic graphical models, e.g. probabilistic networks
- G06N 20/00: Machine learning
- G06Q 10/04: Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem" (market predictions or forecasting for commercial activities G06Q30/0202)
- G06Q 10/0639: Performance analysis of employees; Performance analysis of enterprise or organisation operations
- G06Q 30/02: Marketing; Price estimation or determination; Fundraising
- G06Q 30/0278: {Product appraisal}
- G06Q 30/06: Buying, selling or leasing transactions
- G06Q 50/00: Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism (healthcare informatics G16H)
- G06V 10/7784: {based on feedback from supervisors}
- G06V 10/82: using neural networks
- G16Z 99/00: Subject matter not provided for in other main groups of this subclass
- H02M 1/12: Arrangements for reducing harmonics from AC input or output
- H03M 1/12: Analogue/digital converters ({H03M1/001 – } H03M1/10 take precedence)
- H03M 13/353: {Adaptation to the channel}
- H04B 17/23: Indication means, e.g. displays, alarms, audible means
- H04B 17/26: using historical data, averaging values or statistics
- H04B 17/309: Measuring or estimating channel quality parameters
- H04B 17/318: Received signal strength
- H04B 17/345: Interference values ({signal-to-interference ratio [SIR] or carrier-to-interference ratio [CIR]} H04B17/336)
- H04L 1/0002: {by adapting the transmission rate}
- H04L 1/0041: {Arrangements at the transmitter end}
- H04L 1/18: Automatic repetition systems, e.g. Van Duuren systems
- H04L 1/1854: {Scheduling and prioritising arrangements}
- H04L 1/1874: {Buffer management}
- H04L 67/1097: for distributed storage of data in networks, e.g. transport arrangements for network file system [NFS], storage area networks [SAN] or network attached storage [NAS]
- H04L 67/12: specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
- H04W 4/35: for the management of goods or merchandise
- H04W 4/38: for collecting sensor information
- H04W 4/70: Services for machine-to-machine communication [M2M] or machine type communication [MTC]
- H04W 4/80: Services using short range communication, e.g. near-field communication [NFC], radio-frequency identification [RFID] or low energy communication
- B62D 5/0463: {calculating assisting torque from the motor based on driver input}
- G05B 19/042: using digital processors (G05B19/05 takes precedence)
- G05B 23/02: Electric testing or monitoring
- G05B 23/0208: {characterized by the configuration of the monitoring system}
- G05B 2219/32287: Medical, chemical, biological laboratory
- G05B 2219/35001: Data input, data handling, programming, monitoring of nc
- G05B 2219/37337: Noise, acoustic emission, sound
- G05B 2219/37351: Detect vibration, ultrasound
- G05B 2219/37434: Measuring vibration of machine or workpiece or tool
- G05B 2219/37537: Virtual sensor
- G05B 2219/40115: Translate goal to task program, use of expert system
- G05B 2219/45004: Mining
- G05B 2219/45129: Boring, drilling
- G06F 17/18: for evaluating statistical data {, e.g. average values, frequency distributions, probability functions, regression analysis (forecasting specially adapted for a specific administrative, business or logistic context G06Q10/04)}
- G06F 18/21: Design or setup of recognition systems or techniques; Extraction of features in feature space; Blind source separation
- G06F 18/217: {Validation; Performance evaluation; Active pattern learning techniques}
- G06F 18/25: Fusion techniques
- G06F 2218/00: Aspects of pattern recognition specially adapted for signal processing
- G06N 3/042: Knowledge-based neural networks; Logical representations of neural networks
- G06N 3/126: Evolutionary algorithms, e.g. genetic algorithms or genetic programming
- H01B 17/40: Cementless fittings
- H03M 13/1102: {Codes on graphs and decoding on graphs, e.g. low-density parity check [LDPC] codes}
- H04B 17/29: Performance testing
- H04B 17/40: of relay systems
- H04L 1/0009: {by adapting the channel coding (H04L1/1812 takes precedence)}
- H04L 1/0057: {Block codes (H04L1/0061, H04L1/0064 take precedence)}
- H04L 1/0076: {Distributed coding, e.g. network coding, involving channel coding (coding in both space and time H04L1/0618; cooperative diversity H04B7/022)}
- H04L 5/0064: {Rate requirement of the data, e.g. scalable bandwidth, data priority}
- H04L 67/306: User profiles
- H04L 67/565: Conversion or adaptation of application format or content (adding application control or application functional data H04L67/561)
- H04L 69/163: In-band adaptation of TCP data exchange; In-band control procedures
- H04L 69/164: Adaptation or special uses of UDP protocol
- Y02P 80/10: Efficient use of energy, e.g. using compressed air or pressurized fluid as energy carrier
- Y02P 90/02: Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
- Y02P 90/80: Management or planning
- Y04S 40/18: Network protocols supporting networked applications, e.g. including control of end-device applications over a network
- Y04S 50/00: Market activities related to the operation of systems integrating technologies related to power network operation or related to communication or information technologies
- Y04S 50/12: Billing, invoicing, buying or selling transactions or other related activities, e.g. cost or usage evaluation
- Y10S 707/99939: Privileged access
- G05B: CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS (systems for controlling or regulating non-electric variables G05D; systems for regulating electric or magnetic variables G05F; control devices or systems insofar as characterised by mechanical features only G05G)
- B62D: MOTOR VEHICLES; TRAILERS (steering, or guiding on a desired track, of agricultural machines or implements A01B69/00; wheels, castors, axles, increasing wheel adhesion B60B; vehicle tyres, tyre inflation or tyre changing B60C; connections between vehicles of a train or the like B60D; vehicles for use on rail and road, amphibious or convertible vehicles B60F; suspension arrangements B60G; heating, cooling, ventilating or other air treating devices B60H; windows, windscreens, non-fixed roofs, doors or similar devices, protective coverings for vehicles not in use B60J; propulsion plant arrangements, auxiliary drives, transmissions, controls, instrumentation or dashboards B60K; electric equipment or propulsion of electrically-propelled vehicles B60L; power supply for electrically-propelled vehicles B60M; passenger accommodation not otherwise provided for B60N; adaptations for load transportation or to carry special loads or objects B60P; arrangement of signalling or lighting devices, the mounting or supporting thereof or circuits therefor, for vehicles in general B60Q; vehicles, vehicle fittings or vehicle parts not otherwise provided for B60R; servicing, cleaning, repairing, supporting, lifting, or manoeuvring, not otherwise provided for, B60S; brake arrangements, brake control systems or parts thereof B60T; air-cushion vehicles B60V; motor-cycles, accessories therefor B62J, B62K; testing of vehicles G01M)
- G01M: TESTING STATIC OR DYNAMIC BALANCE OF MACHINES OR STRUCTURES; TESTING OF STRUCTURES OR APPARATUS, NOT OTHERWISE PROVIDED FOR
- G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N)
- G06N: COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06Q: INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06V: IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G16Z: INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS, NOT OTHERWISE PROVIDED FOR
- H02M: APPARATUS FOR CONVERSION BETWEEN AC AND AC, BETWEEN AC AND DC, OR BETWEEN DC AND DC, AND FOR USE WITH MAINS OR SIMILAR POWER SUPPLY SYSTEMS; CONVERSION OF DC OR AC INPUT POWER INTO SURGE OUTPUT POWER; CONTROL OR REGULATION THEREOF (transformers H01F; dynamo-electric converters H02K47/00; controlling transformers, reactors or choke coils, control or regulation of electric motors, generators or dynamo-electric converters H02P)
- H03M: CODING; DECODING; CODE CONVERSION IN GENERAL (using fluidic means F15C4/00; optical analogue/digital converters G02F7/00; coding, decoding or code conversion, specially adapted for particular applications, see the relevant subclasses, e.g. G01D, G01R, G06F, G06T, G09G, G10L, G11B, G11C, H04B, H04L, H04M, H04N; ciphering or deciphering for cryptography or other purposes involving the need for secrecy G09C)
- H04B: TRANSMISSION
- H04L: TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION (arrangements common to telegraphic and telephonic communication H04M)
- H04W: WIRELESS COMMUNICATION NETWORKS (broadcast communication H04H; communication systems using wireless links for non-selective communication, e.g. wireless extensions H04M1/72)
- H01B: CABLES; CONDUCTORS; INSULATORS; SELECTION OF MATERIALS FOR THEIR CONDUCTIVE, INSULATING OR DIELECTRIC PROPERTIES (selection for magnetic properties H01F1/00; waveguides H01P {; printed circuits H05K})
- Y02P: CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y04S: SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y10S: TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS

## Abstract

Systems and methods for data collection and detection of motor noise patterns are disclosed. A system may include a data collector communicatively coupled to at least one input channel, wherein the at least one input channel is operatively coupled to a vibration detection facility structured to detect a motor noise pattern of a motor, a library to store the detected motor noise pattern, an interface circuit structured to make the detected motor noise pattern available to a motor noise pattern data marketplace including a plurality of motor noise patterns from a plurality of motors, and a user interface for accessing at least one of the plurality of motor noise patterns of the motor noise pattern marketplace.

## Claims

### Claim 1

A system, comprising:
a data collector communicatively coupled to at least one input channel, wherein the at least one input channel is operatively coupled to a vibration detection facility structured to detect a motor noise pattern of a motor;
a library to store the detected motor noise pattern;
an interface circuit structured to make the detected motor noise pattern available to a motor noise pattern data marketplace comprising a plurality of motor noise patterns from a plurality of motors; and
a user interface for accessing at least one of the plurality of motor noise patterns of a motor noise pattern marketplace,
wherein the system determines a motor performance parameter based on a match between the detected motor noise pattern and at least one of the plurality of motor noise patterns of the motor noise pattern marketplace, and
wherein the motor performance parameter comprises a vibration phase location.

### Claim 2 (depends on 1)

The system of claim 1, wherein the motor noise pattern marketplace comprises at least one of a data pool or a data stream to provide a plurality of motor noise patterns to the motor noise pattern marketplace.

### Claim 3 (depends on 1)

The system of claim 1, wherein at least one of the plurality of motor noise patterns of the motor noise pattern marketplace comprises a characteristic representative of a motor performance parameter.

### Claim 4 (depends on 3)

The system of claim 3, wherein the motor performance parameter further comprises at least one of a relative phase difference, a vibration amplitude, or a vibration frequency.

### Claim 5 (depends on 1)

The system of claim 1, wherein the motor noise pattern marketplace is a self-organizing marketplace organized based on a machine-learning self-organizing facility that learns based on a measure of marketplace success with respect to stored collected data.

### Claim 6 (depends on 1)

The system of claim 1, wherein the vibration detection facility is further structured to analyze frequency components to assist in detecting the motor noise pattern.

### Claim 7 (depends on 1)

The system of claim 1, wherein the motor noise pattern marketplace receives motor noise patterns from a plurality of data collectors.

### Claim 8 (depends on 1)

The system of claim 1, wherein at least one parameter of the motor noise pattern marketplace is automatically configured by a machine learning facility based on a metric of success of the motor noise pattern marketplace.

### Claim 9 (depends on 8)

The system of claim 8, wherein the metric of success comprises at least one of: a profit measure, a yield measure, a rating, or an indicator of interest.

### Claim 10 (depends on 9)

The system of claim 9, wherein the rating comprises at least one of: a user rating, a purchaser rating, a licensee rating, or a reviewer rating.

### Claim 11 (depends on 9)

The system of claim 9, wherein the indicator of interest comprises at least one of: a clickstream activity, a time spent on a page, a time spent reviewing elements, or a link to a data element.

### Claim 12 (depends on 1)

The system of claim 1, further comprising a rights management engine for managing permissions to access the motor noise pattern in the motor noise pattern marketplace.

### Claim 13 (depends on 1)

The system of claim 1, further comprising a data brokering engine configured to execute a data transaction among at least two motor noise pattern marketplace participants.

### Claim 14 (depends on 1)

The system of claim 1, further comprising a pricing engine for setting a price for at least one data element within the motor noise pattern marketplace.

### Claim 15

A method comprising:
detecting a motor noise pattern of a first motor;
analyzing the detected motor noise pattern to determine a match between the detected motor noise pattern of the first motor and a motor noise pattern of a second motor; and
if a match is determined, setting a motor performance parameter of the first motor to a specified motor performance parameter of the second motor,
wherein the motor noise pattern of the second motor is characteristic of the specified motor performance parameter, and
wherein the motor performance parameter comprises a vibration phase location.

### Claim 16 (depends on 15)

The method of claim 15, further comprising setting an alarm based on the motor performance parameter of the first motor.

### Claim 17 (depends on 16)

The method of claim 16, wherein the motor performance parameter of the first motor further comprises at least one of a relative phase difference, a vibration amplitude, or a vibration frequency.

### Claim 18 (depends on 15)

The method of claim 15, wherein detecting the motor noise pattern comprises at least one of: filtering an incoming signal, signal conditioning, spectral analysis or trend analysis.

### Claim 19 (depends on 15)

The method of claim 15, further comprising isolating vibration noise of the first motor to obtain a vibration fingerprint of the first motor.

### Claim 20 (depends on 15)

The method of claim 15, further comprising:
accessing the motor noise pattern of the second motor using a motor noise pattern marketplace.