Title :
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
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;
Conference_Titel :
Control and Decision Conference (CCDC), 2012 24th Chinese
Conference_Location :
Taiyuan
Print_ISBN :
978-1-4577-2073-4
DOI :
10.1109/CCDC.2012.6244365
