Motor bearing fault diagnosis method and system

Abstract

The invention provides a motor bearing fault diagnosis method and system, and the method comprises the steps of pre-processing a collected continuous vibration fault signal, and obtaining a corresponding fault feature information vector; training the fault feature information vector to obtain a fault classification model; carrying out online classification on the actually measured bearing vibration signals by utilizing the fault classification model, and carrying out digital labeling on each output classification according to a preset labeling rule; analyzing the labels obtained by digital labeling, and outputting the labels representing faults; building a fault diagnosis model of a motor bearing based on a CLPSO-FPN network; training the built fault diagnosis model; and activating a corresponding place in the trained fault diagnosis model according to the output label, and then performing fault diagnosis reasoning according to the trained motor fault diagnosis model. The method of the present invention is used for restraining the problem of space explosion of the complex system fault diagnosis model and improving the adaptability and accuracy of fault diagnosis of the bearing fault diagnosis model.

Description

technical field [0001] The invention relates to the field of motor bearing fault diagnosis, in particular to a motor bearing fault diagnosis method and system. Background technique [0002] The development of science and technology promotes the gradual miniaturization and integration of motors, and the working state of motor bearings directly affects the working efficiency and anti-interference ability of motors. Once the bearing fails, each functional module will have a nonlinear and fuzzy fault relationship, which is not conducive to equipment fault diagnosis and troubleshooting. Therefore, the motor bearing fault diagnosis is very important to the normal operation of the motor. [0003] Traditional motor bearing fault diagnosis methods mainly include quantitative and qualitative methods, among which data-driven based on quantitative analysis is a relatively common fault diagnosis method. For example, in the prior art, a method based on wavelet transform, fuzzy entropy a...

AI Technical Summary

Problems solved by technology

[0005] Aiming at the above-mentioned deficiencies in the prior art, the present invention provides a motor bearing fault diagnosis method and system, which are used to solve the problems of lack of integrity in fault diagnosis of traditional quantitative analysis methods and lack of timeliness in fault diagnosis of qualitative analysis methods, and are used to suppress complex systems. Fault diagnosis model space explosion problem for improving the adaptability of bearing fault diagnosis model and the accuracy of fault diagnosis

Images