Research on fault diagnosis of motor sound signal based on RBF neural network

Junjie Xu; Binbin Li; Feifei Shan; Ruiyao Guo; Tangjia Xie

doi:10.1117/12.2672890

25 April 2023 Research on fault diagnosis of motor sound signal based on RBF neural network

Junjie Xu, Binbin Li, Feifei Shan, Ruiyao Guo, Tangjia Xie

Proceedings Volume 12598, Eighth International Conference on Energy Materials and Electrical Engineering (ICEMEE 2022); 1259830 (2023) https://doi.org/10.1117/12.2672890
Event: Eighth International Conference on Energy Materials and Electrical Engineering (ICMEE 2022), 2022, Guangzhou, China

Abstract

In order to achieve accurate diagnosis of motor faults, a technique based on wavelet analysis and RBF neural networks is used. The wavelet thresholding method is first used to reduce the noise of the motor sound and improve the signal-to-noise ratio in order to further extract fault features. Then the wavelet packet method is used to analyze the sound signals of the three-phase asynchronous motor in three states to extract the band energy, and finally the band energy is fed into the neural network for training to build a classifier for fault diagnosis. The experimental results show that the method of combining wavelet packet technology and RBF neural network has less time consumption and higher accuracy in diagnosing motor faults. It has the potential for further development.

Citation Download Citation

Junjie Xu, Binbin Li, Feifei Shan, Ruiyao Guo, and Tangjia Xie "Research on fault diagnosis of motor sound signal based on RBF neural network", Proc. SPIE 12598, Eighth International Conference on Energy Materials and Electrical Engineering (ICEMEE 2022), 1259830 (25 April 2023); https://doi.org/10.1117/12.2672890

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available