Title :
Study of automobile engine fault diagnosis based on wavelet neural networks
Author :
Weijie, Wang ; Yuanfu, Kang ; Xuezheng, Zhao ; Wentao, Huang
Author_Institution :
Sch. of Mech. & Electr. Eng., Harbin Inst. of Technol., China
Abstract :
The engine vibration signals characters are extracted using wavelet packet technology. A model of wavelet neural networks is constructed based on wavelet frame theory and neural networks technology. Then multiresolution analysis is used to choose and optimize the wavelet neuron. The model is validated through the testing that simulates the faults of engine valve clearance. The experimental results show that the proposed automobile engine fault diagnostic model based on wavelet neural networks can diagnose the engine fault effectively.
Keywords :
automotive components; fault diagnosis; internal combustion engines; mechanical engineering computing; neural nets; signal resolution; vibrations; wavelet transforms; automobile engine fault diagnosis; engine valve clearance; engine vibration signals characters; multiresolution analysis; neural networks technology; wavelet frame theory; wavelet neural networks; wavelet neuron; wavelet packet technology; Automobiles; Engines; Fault diagnosis; Multiresolution analysis; Neural networks; Neurons; Testing; Valves; Wavelet analysis; Wavelet packets;
Conference_Titel :
Intelligent Control and Automation, 2004. WCICA 2004. Fifth World Congress on
Print_ISBN :
0-7803-8273-0
DOI :
10.1109/WCICA.2004.1340976
