SYSTEM AND METHOD FOR PROACTIVE MOTOR WELLNESS DIAGNOSIS BASED ON POTENTIAL MECHANICAL FAULTS
First Claim
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.
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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.
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Citations
20 Claims
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1. A method of detecting impending mechanical faults comprising:
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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. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11)
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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:
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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. - View Dependent Claims (13, 14, 15, 16, 17, 18, 19, 20)
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Specification