SYSTEM AND METHOD FOR PROACTIVE MOTOR WELLNESS DIAGNOSIS BASED ON POTENTIAL MECHANICAL FAULTS

• US 20070005291A1
• Filed: 06/27/2006
• Published: 01/04/2007
• Est. Priority Date: 06/18/2003
• Status: Active Grant

• Current Assignee: Eaton Intelligent Power Limited (Eaton Corporation PLC.)
• Original Assignee: Eaton Corp. (Wisconsin) (Eaton Corporation PLC.)
• Inventors: Krstic, Slobodan, Liu, Yanzhen, Dimino, Steven, Nowak, Michael, Habetler, Thomas, Obaid, Ramzy
• Granted Patent: US 7,346,475 B2
• Time in Patent Office: Days
• US Class Current: 702/145
• CPC Class Codes: G01R 31/343 in operation
• CPC Class Codes: G05B 2219/37351 Detect vibration, ultrasound
• CPC Class Codes: G05B 23/0229 knowledge based, e.g. expert systems; genetic algorithms
• CPC Class Codes: G05B 23/0245 based on a qualitative model, e.g. rule based; if-then decisions
• CPC Class Codes: G05B 23/0254 based on a quantitative model, e.g. mathematical relationships between inputs and outputs; functions: observer, Kalman filter, residual calculation, Neural Networks
• CPC Class Codes: H02H 7/0822 Integrated protection, motor control centres

Abstract

The present invention is directed to a system and method for proactively determining motor wellness arising from potential mechanical faults of the motor. A controller is configured to detect indicia of impending mechanical motor faults. The controller includes a processor configured to determine motor parameters of a given motor including a load and generate a set of baseline data for the given motor. The processor is also configured to acquire current spectrum data from the given motor during operation, map at least one from a plurality of load bins based on the load, and generate a mechanical fault signature from the current spectrum. The processor is caused to compare the mechanical fault signature to baseline data from the set of baseline data corresponding to the mapped bin and determine amplitude variances within the mechanical fault signature indicative of an impending mechanical fault prior to an actual mechanical fault occurrence.

Claims

1. A method of detecting impending mechanical faults comprising:

generating baseline data for an operating motor;

receiving a first set of current data from the operating motor;

performing an FFT on the first set of current data to generate a first set of frequency spectrum data;

receiving a second set of current data from the operating motor;

performing an FFT on the second set of current data to generate a second set of frequency spectrum data;

linearly averaging the first set of frequency spectrum data with the second set of frequency spectrum data to generate an averaged set of frequency spectrum data;

selecting a first range of frequency spectrum data from the averaged set of frequency spectrum data, the first range comprising frequencies greater than a system frequency;

summing the frequency spectrum data within the first range to generate a mechanical fault signature;

comparing the mechanical fault signature to a portion of the baseline data; and

determining amplitude variances within a component of a running shaft speed of the motor indicative of prospective faults due to at least one of motor misalignment and unbalance.

2. The method of claim 1 further comprising:

determining an average power of the operating motor;

determining a load of the operating motor;

mapping the average power of the operating motor to a load bin based on the load of the operating motor; and

selecting a portion of the baseline data for comparison to the summed frequency data based on the mapped load bin.

3. The method of claim 1 further comprising:

receiving at least another set of current data from the operating motor;

performing an FFT on the at least another set of current data to generate at least another set of frequency spectrum data; and

wherein the step of linearly averaging further comprises linearly averaging the first set of frequency spectrum data with the second set of frequency spectrum data and with the at least another set of frequency spectrum data to generate the averaged set of frequency spectrum data.

4. The method of claim 1 further comprising:

selecting a second range of frequency spectrum data from the averaged set of frequency spectrum data, the second range comprising frequencies lower than a system frequency;

summing the frequency spectrum data within the second range to generate a second mechanical fault signature;

linearly averaging the first mechanical fault signature with the second mechanical fault signature to generate an averaged mechanical fault signature; and

wherein the step of summing comparing the mechanical fault signature to a portion of the baseline data comprises comparing the averaged mechanical fault signature to a portion of the baseline data.

5. The method of claim 1 further comprising performing at least one of an RSS value calculation and a polynomial estimation to compensate for energy leakage within the current data.

6. The method of claim 5 further comprising estimating an instantaneous amplitude of running shaft speed components as a function of neighboring running shaft speed components to perform polynomial estimation.

7. The method of claim 6 wherein the neighboring running shaft speed components include at least one upper running shaft speed component and at least one lower running shaft speed component.

8. The method of claim 5 further comprising performing the RSS value calculation for a plurality of frequency components in the first range of frequency spectrum data.

9. The method of claim 1 further comprising generating a ratio of the mechanical fault signature to the baseline data indicating a probability of the prospective faults.

10. The method of claim 9 further comprising communicating a wellness alert to an operator display if the ratio is greater than a threshold.

11. The method of claim 10 further comprising communicating the wellness alert to the operator display over a communications bus of a system including the operating motor.

12. A computer readable storage medium having stored thereon a computer program comprising instructions which, when executed by at least one processor, cause the at least one processor to:

receive at least two sets of operational current data from a motor;

perform an FFT for each of the at least two sets of operational current data to generate frequency spectrum data for each of the at least two sets of operational current data;

average the frequency spectrum data of the at least two sets of operational current data to generate an averaged frequency spectrum;

generate a mechanical fault signature from the averaged frequency spectrum data;

if in a learning mode, compile a baseline from the mechanical fault signature; and

if not in the learning mode;

determine a load of the motor;

acquire the baseline corresponding to a mapped load bin based on the load of the operating motor;

compare a portion of the baseline to the mechanical fault signature; and

determine an impending mechanical fault before a fault occurrence.

13. The computer program of claim 12 wherein the processor is further caused to select at least one sideband within the averaged frequency spectrum data on at least one side of a system frequency of the motor and determine amplitude variances within the at least one sideband indicative of an impending mechanical fault.

14. The computer program of claim 12 wherein the processor is further caused to communicate a wellness alert upon detecting amplitude variances indicative of future mechanical faults.

15. The computer program of claim 14 wherein the processor is further caused to communicate the wellness alert to an operator display over a communications bus of a system including the motor.

16. The computer program of claim 12 wherein the processor is further caused to compensate for energy leakage in the averaged frequency spectrum data.

17. The computer program of claim 16 wherein the processor is further caused to perform at least one of an RSS value calculation and a polynomial estimation to compensate for the energy leakage within the averaged frequency spectrum data.

18. The computer program of claim 17 wherein the processor is further caused to estimate an instantaneous amplitude of running shaft speed components within the averaged frequency spectrum data as a function of neighboring running shaft speed components to perform polynomial estimation.

19. The computer program of claim 17 wherein the processor is further caused to perform the RSS value calculation for a plurality of frequency components in a selected frequency band surrounding a running frequency of the motor.

20. The computer program of claim 12 wherein the processor is further caused to:

compile baseline power data;

receive at least two sets of operational power data from the motor;

perform an FFT on each of the at least two sets of operational power data to generate power spectrum data for each of the at least two sets of operational power data;

average the power spectrum data of the at least two sets of operational power data to generate an averaged power spectrum data;

generate a mechanical fault signature from the averaged power spectrum data;

compare a portion of the baseline power data corresponding to a mapped load bin to the averaged power spectrum data; and

determine an impending mechanical fault before a fault occurrence.