Fault detection system and associated method

• US 9,645,046 B2
• Filed: 12/17/2012
• Issued: 05/09/2017
• Est. Priority Date: 12/17/2012
• Status: Active Grant

• Current Assignee: GE Infrastructure Technology, LLC (General Electric Company)
• Original Assignee: General Electric Company
• Inventors: Zhang, Pinjia, Neti, Prabhakar
• Primary Examiner(s): BHAT, ADITYA S
• Application Number:
  US13/716,933
• Publication Number:
  US 20140172326A1
• Time in Patent Office: 1,604 Days
• Field of Search: None
• CPC Class Codes: G01M 13/00 Testing of machine parts
• CPC Class Codes: G01M 13/04 Bearings
• CPC Class Codes: G01R 31/343 in operation
• CPC Class Codes: G06F 17/00 Digital computing or data processing equipment or methods, specially adapted for specific functions information retrieval, database structures or file system structures therefor G06F16/00

Abstract

A method implemented using a processor based device includes obtaining a measured electrical signal from an electrical device coupled to a mechanical device and generating a signal signature representative of a fault in the mechanical device based on the measured electrical signal. The method also includes determining a diagnostic parameter based on a harmonic frequency of the signal signature and determining the fault in the mechanical device based on the diagnostic parameter.

Claims

1. A method, comprising:

using a sensor for obtaining a measured electrical signal from an electrical device comprising an electrical generator coupled to a mechanical device comprising a mechanical drive train, wherein the measured electrical signal is representative of torsional vibrations generated by the mechanical device;

generating a signal signature representative of a bearing fault of a bearing in the mechanical device based on the measured electrical signal;

determining a diagnostic parameter based on a harmonic frequency of the signal signature, geometric dimensions of the bearing, and operating parameters of the mechanical drive train;

determining the bearing fault in the mechanical device based on the diagnostic parameter and taking a corrective action in response to the determined bearing fault.

2. The method of claim 1, wherein the measured electrical signal is representative of at least one of a measured current and a measured voltage of the electrical device.

3. The method of claim 1, wherein generating the signal signature comprises determining a spectrum of the electrical signal.

4. The method of claim 1, wherein determining the bearing fault in the mechanical device_comprises comparing the diagnostic parameter with a predefined threshold value.

5. The method of claim 1, wherein generating the signal signature comprises determining at least one of a fast fourier transform, a discrete fourier transform, a wavelet transform, a power spectral density of the electrical signal.

6. The method of claim 1, wherein determining the diagnostic parameter comprises:

determining a frequency range corresponding to a type of the bearing fault of the bearing in the mechanical device; and

determining a magnitude of the signal signature corresponding to the determined frequency range.

7. The method of claim 6, wherein the magnitude is representative of at least one of an average value, a peak value, or a median value of the signal signature.

8. The method of claim 1, wherein determining the bearing fault of the bearing in the mechanical device comprises determining at least one of a type of the bearing fault and a severity of the bearing fault.

9. The method of claim 8, wherein determining the type of the bearing fault comprises:

determining a peak magnitude of the signal signature;

identifying a frequency range of the signal signature, corresponding to the peak magnitude; and

determining at least one of an outer race defect, an inner race defect, and a ball damage based on the identified frequency range.

10. The method of claim 8, wherein determining the severity of the bearing fault comprises:

identifying a frequency range of the signal signature, corresponding to the type of the bearing fault of the bearing in the mechanical device;

determining a peak magnitude of the signal signature, corresponding to the frequency range; and

determining the severity of the bearing fault based on the determined peak magnitude.

11. The method of claim 1, wherein the operating parameters of the mechanical drive train comprise a rotational speed of a shaft and the dimensions of the bearing comprise a gear ratio of an intermediate gear of the mechanical drive train.

12. A system comprising:

a mechanical device comprising a mechanical drive train;

an electrical device comprising an electrical generator coupled to the mechanical device;

a sensor for obtaining a measured electrical signal representative of torsional vibrations generated by the mechanical device; and

a processor based device configured to;

receive the measured electrical signal;

generate a signal signature representative of a bearing fault of a bearing in the mechanical device based on the measured electrical signal;

determine a diagnostic parameter based on a harmonic frequency of the signal signature, geometric dimensions of the bearing, and operating parameters of the mechanical drive train;

determine the bearing fault in the mechanical device based on the diagnostic parameter and taking a corrective action in response to the determined bearing fault.

13. The system of claim 12, wherein the measured electrical signal is representative of at least one of a measured current and a measured voltage of the electrical device.

14. The system of claim 12, wherein the processor based device is configured to generate the signal signature by determining a spectrum of the electrical signal.

15. The system of claim 12, wherein the processor based device is further configured to determine the bearing fault of the bearing in the mechanical device by comparing the diagnostic parameter with a predefined threshold value.

16. The system of claim 12, wherein the processor based device is configured to generate the signal signature by determining at least one of a fast fourier transform, a discrete fourier transform, a wavelet transform, and power spectral density of the electrical signal.

17. The system of claim 12, wherein the processor based device is further configured to:

determine a frequency range corresponding to a type of the bearing fault; and

determine a magnitude of the signal signature corresponding to the determined frequency range.

18. The system of claim 17, wherein the processor based device is configured to determine the magnitude by computing at least one of an average value, a peak value, a median value of the signal signature.

19. The system of claim 12, wherein the processor based device is configured to determine the bearing fault of the bearing in the mechanical device by determining at least one of a type of the bearing fault and a severity of the bearing fault.

20. The system of claim 19, wherein the processor based device is configured to:

determine a peak magnitude of the signal signature;

identify a frequency range of the signal signature, corresponding to the peak magnitude; and

determine the type of the bearing fault comprising at least one of an outer race defect, an inner race defect, and a ball damage based on the identified frequency range.

21. The system of claim 19, wherein the processor based device is configured to:

identify a frequency range of the signal signature, corresponding to the type of the bearing fault of the bearing in the mechanical device;

determine a peak magnitude of the signal signature, corresponding to the frequency range; and

determine the severity of the bearing fault based on the determined peak magnitude.

22. The system of claim 12, wherein the operating parameters of the mechanical drive train comprise a rotational speed of a shaft and the dimensions of the bearing comprise a gear ratio of an intermediate gear of the mechanical drive train.

23. A non-transitory computer readable medium encoded with a program to instruct a processor based device to:

obtain a measured electrical signal from an electrical device comprising an electrical generator coupled to a mechanical device comprising a mechanical drive train, wherein the measured electrical signal is obtained using a sensor and is representative of torsional vibrations generated by the mechanical device;

generate a signal signature representative of a bearing fault of a bearing in the mechanical device based on the measured electrical signal;

determine a diagnostic parameter based on a harmonic frequency of the signal signature, geometric dimensions of the bearing, and operating parameters of the mechanical drive train;

determine the bearing fault in the mechanical device based on the diagnostic parameter and taking a corrective action in response to the determined bearing fault.