Method for estimating bearing fault severity for induction motors

Patent metadata

Field	Value
Publication number	US-11099101-B2
Application number	US-201916515564-A
Country	US
Kind code	B2
Filing date	Jul 18, 2019
Priority date	May 3, 2019
Publication date	Aug 24, 2021
Grant date	Aug 24, 2021

Abstract

A system for estimating a severity of a bearing fault in an induction motor, uses a set of filters and a set of quantitative models designed for a set of fault frequencies. The system, upon receiving the measurements of the stator current, extracts the first fault current from the stator current using the first filter, determine the first mutual inductance variation from the first fault current using the first quantitative model, and classify the first mutual inductance variation with the fault severity classifier to determine the severity of a first type of fault in the induction motor. Similarly, the system classifies a second type of fault using the second filter and the second quantitative model. The system outputs one or combination of the severity of the first type of fault in the induction motor and the severity of the second type of fault in the induction motor.

First claim

We claim:

1. A system for estimating a severity of a bearing fault in an induction motor, comprising:
an input interface configured to accept measurements of a stator current during an operation of the induction motor;
a memory configured to store a set of filters, each filter is configured to extract a fault current of a fault frequency from the stator current, the set of filters includes a first filter to extract a first fault current of a first fault frequency and a second filter to extract a second fault current of a second fault frequency; and
a set of quantitative models, each quantitative model is configured to relate the fault current of the fault frequency to a mutual inductance variation for the fault frequency, the set of quantitative models includes a first quantitative model to relate a magnitude of the first fault current to a first mutual inductance variation for the first fault frequency and a second quantitative model to relate the second fault current to a second mutual inductance variation for the second fault frequency; at least one fault severity classifier for estimating a severity of the fault in the induction motor for each of the fault frequency based on the mutual inductance variation for the fault frequency;
a processor configured, upon receiving the measurements of the stator current, to extract the first fault current from the stator current using the first filter, determine the first mutual inductance variation from the first fault current using the first quantitative model, and classify the first mutual inductance variation with the fault severity classifier to determine the severity of a first type of fault in the induction motor; and extract the second fault current from the stator current using the second filter, determine the second mutual inductance variation from the second fault current using the second quantitative model, and classify the second mutual inductance variation with the fault severity classifier to determine the severity of a second type of fault in the induction motor; and
an output interface configured to output one or combination of the severity of the first type of fault in the induction motor and the severity of the second type of fault in the induction motor,
wherein each quantitative model approximates the mutual inductance variation for the fault frequency using Fourier Series of a set of oscillating functions of the fault frequency, wherein a frequency of each oscillating function in the Fourier Series is a multiple of the fault frequency, and an amplitude of each oscillating function in the Fourier Series is a function of a magnitude of the fault current on the fault frequency, such that the first quantitative model approximates the first mutual inductance variation using oscillating functions of multiples of the first fault frequency with amplitudes of the function of the magnitude of the first fault current, and the second quantitative model approximates the second mutual inductance variation using oscillating functions of multiple of the second fault frequency with amplitudes of the function of the magnitude of the second fault current.

2. The system of claim 1 , wherein the set of oscillating functions of multiples of the fault frequency is a set of cosine functions of multiples of the fault frequency.

3. The system of claim 2 , wherein the set of cosine functions of multiples of the fault frequency includes only a first order cosine function.

4. The system of claim 1 , wherein the measurements of the stator current are sampled with a sampling rate of at least twice of the first fault frequency, if the first fault frequency is greater than the second fault frequency, or sampled with a sampling rate of at least twice of the second fault frequency, if the second fault frequency is greater than the first fault frequency.

5. The system of claim 1 , wherein to extract the fault current of the fault frequency from the stator current each filter is configured to perform Park transformation of the measurements of the stator current to produce a transformed stator current; filter fundamental components of the stator current from the transformed stator current to produce a stator current residue; and extract the faulty frequency from the stator current residue using a band-pass filter to produce the faulty current of the faulty frequency.

6. The system of claim 1 , wherein a transfer function of the mutual inductance variation maps the mutual inductance variation to a permeance of an air gap between a stator and a rotor of the induction motor, such that the set of thresholds specify a set of values of the permeance of the air gap.

7. The system of claim 1 , wherein a transfer function of the mutual inductance variation maps the mutual inductance variation to a length profile of an air gap between a stator and a rotor of the induction motor, such that the set of thresholds specify a set of values of the maximum variation in the length profile of the air gap.

8. The system of claim 1 , wherein a fault severity classifier compares a transfer function of the first and the second mutual inductance variations with at least one threshold from the set of thresholds to determine the severity of the first and the second type of fault in the induction motor.

9. The system of claim 8 , wherein the induction motor does not have the first type of fault when the transfer function of the first mutual inductance variation is less than a first threshold, wherein the induction motor has the first type of fault allowing to continue the operation of the induction motor when the transfer function of the first mutual inductance variation is less than a second threshold, and wherein the processor is configured to stop the operation of the induction motor when the transfer function of the first mutual inductance variation is greater than the second threshold.

10. The system of claim 1 , wherein the processor is configured to determine a function of air gap variations in the induction motor, including a function of a frequency of the air gap variations and a function of a magnitude of the air gap variations; determine the type of the fault from the frequency of the air gap variations; and determine the severity of the fault from the magnitude of the air gap variations.

11. A method for estimating a severity of a bearing fault in an induction motor, wherein the method uses a processor coupled to a memory storing a set of filters, each filter is configured to extract a fault current of a fault frequency from the stator current, the set of filters includes a first filter to extract a first fault current of a first fault frequency and a second filter to extract a second fault current of a second fault frequency; a set of quantitative models, each quantitative model is configured to relate the fault current of the fault frequency to a mutual inductance variation for the fault frequency, the set of quantitative models includes a first quantitative model to relate a magnitude of the first fault current to a first mutual inductance variation for the first fault frequency and a second quantitative model to relate the second fault current to a second mutual inductance variation for the second fault frequency; and at least one fault severity classifier for estimating a severity of the fault in the induction motor for each of the fault frequency based on the mutual inductance variation for the fault frequency, wherein the processor is coupled with stored instructions implementing the method, wherein the instructions, when executed by the processor carry out steps of the method, comprising:
accepting measurements of a stator current during an operation of the induction motor;
extracting the first f

Assignees

• Mitsubishi Electric Res Laboratories Inc
• Mitsubishi Electric Corp

Inventors

• Wang Bingnan
• Zhang Shen
• Kanemaru Makoto
• Lin Chungwei
• Liu Dehong
• Teo Koon Hoo

Classifications

• G01R31/343

  in operation · CPC title

• H02H3/50

  responsive to the appearance of abnormal wave forms, e.g. AC in DC installations · CPC title

• H02H7/08

  for dynamo-electric motors · CPC title

• G01M13/04 Primary

  Bearings · CPC title