Touch screen-based motor bearing fault diagnosis

Author

Fu, Lijun ; Qian, Zhenhai ; Tang, Yan ; Zhu, Meichen ; Liu, Hongbin

Author_Institution

Sch. of Inf. Sci. & Eng., Shenyang Ligong Univ., Shenyang, China

fYear

2012

fDate

23-25 May 2012

Firstpage

2275

Lastpage

2280

Abstract

A combined method with wavelet packet and BP neural network based on touch screen for motor bearing fault diagnosis is presented. Firstly, this method uses the time-frequency technology of wavelet packet for the feature extraction of motor vibration signals. Secondly, BP neural network is designed based on energy feature vector, and the algorithm is realized with MATLAB software. Finally, diagnostic results are displayed on the touch screen, which is based on three typical running states of motor rotor system. Simulation studies show that the proposed algorithm is reliable, and efficient.

Keywords

acoustic signal detection; backpropagation; electric machine analysis computing; electric motors; fault diagnosis; feature extraction; machine bearings; neural nets; rotors; time-frequency analysis; touch sensitive screens; vibrations; wavelet transforms; BP neural network; MATLAB software; energy feature vector; feature extraction; motor rotor system; motor vibration signals; time-frequency technology; touch screen-based motor bearing fault diagnosis; wavelet packet; Induction motors; Neural networks; Neurons; Wavelet analysis; Wavelet domain; Wavelet packets; BP Neural Network; Fault Diagnosis; Touch Screen; Wavelet Packet Analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Control and Decision Conference (CCDC), 2012 24th Chinese

Conference_Location

Taiyuan

Print_ISBN

978-1-4577-2073-4

Type

conf

DOI

10.1109/CCDC.2012.6244365

Filename

6244365