Title :
Aerocraft fault diagnosis based on wavelet neural network
Author :
Hou Xia ; Zhang Junfeng ; Liu Guohai
Author_Institution :
Sch. of Electr. & Inf. Eng., Jiangsu Univ., Zhenjiang, China
Abstract :
Based on the strong learning ability and generalization characteristics of wavelet neural network, the familiar failure of aerocraft is detected seperately on line by normal wavelet neural network and BP neural network. The simulation result shows this method of aerocraft fault diagnosis with wavelet neural network is feasible, effective and preferable.
Keywords :
aircraft; backpropagation; fault diagnosis; neural nets; wavelet transforms; BP neural network; aerocraft fault diagnosis; wavelet neural network; Adaptation model; Artificial neural networks; Biological neural networks; Brain modeling; Computational modeling; Electronic mail; Fault diagnosis; BP Neural Network; Fault Diagnosis; Wavelet Neural Network;
Conference_Titel :
Control Conference (CCC), 2010 29th Chinese
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-6263-6
