IP Library Granted Patent US 11,199,835
Granted Patent B2
US 11,199,835 · App. 16/235,966 · Granted Dec 14, 2021

Method and system of a noise pattern data marketplace in an industrial environment

Inventors: Charles Howard Cella (Pembroke, MA); Gerald William Duffy, Jr. (Philadelphia, PA); Jeffrey P. McGuckin (Philadelphia, PA); Mehul Desai (Oak Brook, IL)
Assignee: Strong Force IoT Portfolio 2016, LLC
G05B23/0221G01M13/028G01M13/04G01M13/045G05B13/028G05B19/4183G05B19/4184G05B19/4185G05B19/41845G05B19/41865G05B19/41875G05B23/024G05B23/0229G05B23/0264G05B23/0283G05B23/0286G05B23/0289G05B23/0291G05B23/0294G05B23/0297G06K9/6263G06N3/006G06N3/02G06N3/0445G06N3/0454G06N3/0472G06N3/084G06N3/088G06N5/046G06N7/005G06N20/00G06Q10/04G06Q10/0639G06Q30/02G06Q30/0278G06Q30/06G06Q50/00G16Z99/00H04B17/23H04B17/309H04B17/318H04B17/345H04L1/0002H04L1/0041H04L1/18H04L1/1874H04L67/1097H04L67/12H04W4/38H04W4/70G05B19/042G05B23/02G05B23/0208G05B2219/32287G05B2219/35001G05B2219/37337G05B2219/37351G05B2219/37434G05B2219/37537G05B2219/40115G05B2219/45004G05B2219/45129G06K9/6217G06K9/6262G06K9/6288G06N3/126H04B17/29H04B17/40H04L1/0009H04L5/0064H04L67/306Y02P80/10Y02P90/02Y02P90/80Y04S50/00Y04S50/12Y10S707/99939
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Quick Facts
Patent No.
US 11,199,835
App. No.
16/235,966
Granted
Dec 14, 2021
Kind
B2
Abstract

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

Claims (31)

1. A system comprising:

a data collector communicatively coupled to a plurality of input channels, wherein at least one of the plurality of input channels is operatively coupled to a vibration detection facility structured to detect a noise pattern of an industrial machine;

a library to store the detected noise pattern;

an interface circuit structured to make the noise pattern available to a noise pattern marketplace, the noise pattern marketplace comprising a plurality of noise patterns from a plurality of industrial machines; and

a user interface for accessing the plurality of noise patterns of the noise pattern marketplace,

wherein the system is configured to identify a machine performance category based on a match between the detected noise pattern and one of the plurality of noise patterns of the noise pattern marketplace.

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

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

4. The system of claim 3 , wherein the machine performance category comprises a machine start-up category, a machine shut-down category, a normal machine operation category, or an operational failure mode category.

5. The system of claim 1 , wherein the user interface enables the identification of the machine performance category based on the match between the detected noise pattern and one of the plurality of noise patterns of the noise pattern marketplace.

6. The system of claim 1 , wherein the 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.

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

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

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

10. The system of claim 9 , wherein the metric of success comprises at least one of: a profit measure, a yield measure, a rating, or an indicator of interest.

11. The system of claim 10 , wherein the rating comprises at least one of: a user rating, a purchaser rating, a licensee rating, or a reviewer rating.

12. The system of claim 10 , wherein the indicator of interest comprises at least one of: a clickstream activity, a time spent on a page, a time spent reviewing elements, and a link to data elements.

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

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

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

16. A method comprising:

detecting a noise pattern of a first industrial machine;

analyzing the detected noise pattern to determine a match between the detected noise pattern of the first industrial machine and a noise pattern of a second industrial machine stored in a library;

when a match is determined, setting a machine performance category of the first industrial machine to a specified machine performance category of the second industrial machine,

wherein the noise pattern of the second industrial machine is characteristic of the specified machine performance category; and

after the match is determined, updating the library to apply a rule for comparing noise patterns when the detected noise pattern is associated with a different machine performance category than the specified machine performance category.

17. The method of claim 16 , further comprising setting an alarm based on the machine performance category of the first industrial machine.

18. The method of claim 17 , wherein the machine performance category of the first industrial machine comprises a machine start-up category, a machine shut-down category, a normal machine operation category, or an operational failure mode category.

19. The method of claim 16 , wherein detecting a noise pattern comprises at least one of: filtering an incoming signal, signal conditioning, spectral analysis and trend analysis.

20. The method of claim 16 , further comprising isolating vibration noise of the first industrial machine to obtain a vibration fingerprint of the machine.

21. The system of claim 6 , wherein the self-organizing facility learns based on the measure of marketplace success such that the self-organizing marketplace is progressively configured to promote noise patterns that accurately predict a machine performance category.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Apr 24, 2020
From: CELLA, CHARLES HOWARD; DUFFY, GERALD WILLIAM, JR; MCGUCKIN, JEFFREY P.; DESAI, MEHUL
To: STRONG FORCE IOT PORTFOLIO 2016, LLC
Reel/Frame 052486/0898 →
Continuity (14)
Continuation 16143286 · Sep 26, 2018
Continuation 15973406 · May 7, 2018
Continuation In Part PCTUS2017031721 · May 9, 2017
Continuation PCTUS2018045036 · Aug 2, 2018
Continuation 15973406 · May 7, 2018
Provisional Application 62333589 · May 9, 2016
Provisional Application 62350672 · Jun 15, 2016
Provisional Application 62412843 · Oct 26, 2016
Provisional Application 62427141 · Nov 28, 2016
Provisional Application 62540557 · Aug 2, 2017
Provisional Application 62562487 · Sep 24, 2017
Provisional Application 62583487 · Nov 8, 2017
Provisional Application 62540513 · Aug 2, 2017
Related Publication 20190155263A1 · May 23, 2019
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