Motor fault diagnosis method and system

Abstract

The invention relates to the field of motor fault diagnosis, and discloses a motor fault diagnosis method and system, which can find abnormal conditions of motor operation in time and perform fault diagnosis, and is convenient to use and easy to implement. The method comprises the following steps of selecting a normal training data set, calculating a first detection statistic, and calculating a detection threshold; selecting different types of fault data as a fault training data set, calculating a second detection statistic, calculating a fault probability density function of the second detection statistic by adopting a kernel density estimation method, and constructing a probability density function set of all types of fault samples; selecting a test data set, calculating a third detection statistic according to the test data set, comparing the third detection statistic with a detection threshold, and judging whether the motor has a fault or not; and if a fault occurs, calculating a fault density function of the third detection statistics by adopting a kernel density estimation method, and constructing a probability density function set of the test data set so as to diagnose the fault type.

Description

technical field [0001] The invention relates to the field of motor fault diagnosis, in particular to a motor fault diagnosis method and system. Background technique [0002] Motor is a kind of electrical equipment widely used in various industries, such as high-speed train traction drive system, wind power generator, new energy vehicle drive motor, rail traction motor, ship motor, etc. In practical applications, because the motor is affected by factors such as frequent start-up, load fluctuation, and harsh working environment, the motor running state is abnormal and inevitably fails. If these failures are not diagnosed and found in time, they will continue to deteriorate and eventually lead to the failure of the entire system, which will bring huge losses to industrial production. [0003] In the actual operation of the motor, such as switching between startup acceleration, constant speed, braking deceleration and other states, the dynamic characteristics of different worki...

AI Technical Summary

Problems solved by technology

In practical applications, because the motor is affected by factors such as frequent start-up, load fluctuations, and harsh working environment, the motor's operating state is abnormal and inevitably fails.

If these failures are not diagnosed and found in time, they will continue to deteriorate and eventually lead to the failure of the entire system, causing huge losses to industrial production

[0003] In the actual operation of the motor, such as switching between startup acceleration, constant speed, braking deceleration and other states, the dynamic characteristics of different working conditions are different, and the changes of system parameters and measurement data are complicated.

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