Prognostics and life estimation of electrical machines

Patent metadata

Field	Value
Publication number	US-9255969-B2
Application number	US-201213476545-A
Country	US
Kind code	B2
Filing date	May 21, 2012
Priority date	May 21, 2012
Publication date	Feb 9, 2016
Grant date	Feb 9, 2016

Abstract

The method includes measuring an operating parameter comprising at least one of a phasor current and phasor voltage of an electrical machine. The method further includes determining a diagnostic parameter indicative of a fault of the electrical machine based on the measured operating parameter. The method also includes estimating end of life of the electrical machine based on the diagnostic parameter using an error minimization method.

First claim

What is claimed as new and desired to be protected by Letters Patent of the United States is:

1. A method, comprising:
measuring an operating parameter comprising at least one of a phasor current and phasor voltage of an electrical machine;
determining a diagnostic parameter indicative of a fault of the electrical machine based on the measured operating parameter by computing a plurality of present values indicative of the diagnostic parameter, each present value corresponding to a time instant during operation of the electrical machine;
selecting a data model for the diagnostic parameter;
estimating at least one constant of the data model based on the plurality of present values indicative of the diagnostic parameter;
estimating a future value indicative of the diagnostic parameter using the at least one estimated constant of the data model;
estimating end of life of the electrical machine when the future value exceeds a pre-determined threshold value; and
controlling the operating parameter of the electrical machine based on the estimated end of life.

2. The method of claim of 1 , wherein the phasor current is a three phasor current and the phasor voltage is a three phasor voltage, and wherein determining the diagnostic parameter comprises:
determining a positive sequence voltageand a negative sequence voltage based on the measured three phasor voltage;
determining a positive sequence current and a negative sequence current based on the measured three phasor current; and
determining a cross-coupled impedance indicative of the fault of at least one stator winding of the electrical machine, based on the determined positive sequence voltage, the negative sequence voltage, the positive sequence current and the negative sequence current.

3. The method of claim of 1 , wherein determining the diagnostic parameter comprises:
determining a signature current based on the measured phasor current;
determining a frequency spectrum based on the signature current; and
determining a spectral peak value indicative of the fault of a rotor bar of the electrical machine based on a sideband of the frequency spectrum.

4. The method of claim of 1 , wherein determining the diagnostic parameter comprises:
determining a signature current based on the measured phasor current;
determining a frequency spectrum based on the determined signature current;
selecting a frequency band corresponding to a fault of a bearing of the electrical machine, from a sideband of the frequency spectrum; and
determining a Root Mean Square (RMS) value indicative of the fault of the bearing based on a plurality of sample values of the selected frequency band.

5. The method of claim 1 , wherein the fault associated with the electrical machine comprises at least one of a stator fault, a rotor bar fault, and a bearing fault.

6. The method of claim 1 , wherein the diagnostic parameter comprises at least one of across coupled impedance, a spectral peak magnitude, and an RMS value based on the measured operating parameter of the electrical machine.

7. The method of claim 1 , further comprising normalizing the diagnostic parameter.

8. The method of claim 1 , wherein the data model is an exponential model.

9. The method of claim 1 , further comprising determining the pre-determined threshold value based on plurality of factors comprising a rated life of the electrical machine, type of application, required safety margin, degradation of the electrical machine.

10. The method of claim 1 , further comprising determining the data model based on a Least Squares (LS) method or a Weighted Least Squares (WLS) method.

11. A system comprising:
a current sensor for measuring a phasor current of an electrical machine;
a voltage sensor for measuring a phasor voltage of the electrical machine; and
a fault estimation module communicatively coupled to the current sensor and the voltage sensor and configured to:
determine a diagnostic parameter indicative of a fault of the electrical machine based on at least one of the measured phasor current and the phasor voltage by computing a plurality of present values indicative of the diagnostic parameter, each present value corresponding to a time instant during operation of the electrical machine;
select a data model for the diagnostic parameter;
estimate at least one constant of the data model based on the plurality of present values indicative of the diagnostic parameter;
estimate a future value indicative of the diagnostic parameter using the at least one estimated constant of the data model;
estimate end of life when the future value indicative of the diagnostic parameter exceeds a pre-determined threshold value; and
control at least one of the phasor current and the phasor voltage of the electrical machine based on the estimated end of life.

12. The system of claim 11 , further comprising a memory communicatively coupled with the fault estimation module and capable of storing the diagnostic parameter.

13. The system of claim 11 , wherein the fault comprises at least one of a stator turn fault, a rotor bar fault, and a bearing fault.

14. The system of claim 11 , wherein the fault estimation module is configured to compute the diagnostic parameter comprising at least one of a cross coupled impedance, a spectral peak magnitude, an RMS value based on at least one of the measured current and voltage of the electrical machine.

15. The system of claim 11 , wherein the fault estimation module is configured to estimate the data model for the diagnostic parameter.

16. The system of claim 11 , wherein the phasor current is a three phasor current and the phasor voltage is a three phasor voltage, wherein the fault estimation module is further configured to:
determine a positive sequence voltage and a negative sequence voltage based on the measured three phasor voltages;
determine a positive sequence current and a negative sequence current based on the measured three phasor currents;
determine a cross coupled impedance indicative of the fault of at least one stator winding of the electrical machine, based on the determined positive sequence voltage, negative sequence voltage, positive sequence current and the negative sequence current.

17. The system of claim 11 , wherein the fault estimation module is further configured to:
determine a signature current based on the measured phasor current;
determine a frequency spectrum based on the signature current;
determine a spectral peak value indicative of the fault of a rotor bar of the electrical machine based on a sideband of the frequency spectrum.

18. The system of claim 11 , wherein the fault estimation module is further configured to:
determine a signature current based on the measured phasor current;
determine a frequency spectrum based on the determined signature current;
select a frequency band corresponding to a fault of a bearing of the electrical machine, from a sideband of the frequency spectrum;
determine a Root Mean Square (RMS) value indicative of the fault of the bearing based on a plurality of sample values of the selected frequency band.

19. The system of claim 11 , wherein the fault estimation module is further configured to normalize the diagnostic parameter.

20. A non-transitory computer readable medium encoded with a program to instruct a processing unit to:
measure an operating parameter comprising at least one of a phasor current and a phasor voltage of an electrical machine;
determine a diagnostic parameter indicative of a fault of

Assignees

• Basu Wrichik
• Ramachandrapanicker Somakumar
• Patel Dhaval Chandubhai
• Karambatos Demetrios
• Deveaux Robert Charles
• Allcock David John
• Banerjee Arijit
• Gen Electric

Inventors

• Basu Wrichik
• Ramachandrapanicker Somakumar
• Patel Dhaval Chandubhai
• Karambatos Demetrios
• Deveaux Robert Charles
• Allcock David John
• Banerjee Arijit

Classifications

• G01R31/343 Primary

  in operation · CPC title