Nonlinear analog-circuit fault diagnosis based on HAAR wavelet and neural-network

被引：0
|
作者：
Xie, H [1 ]
He, YG [1 ]
Wu, J [1 ]
机构：
[1] Hunan Univ, Fac Elect & Informat Engn, Changsha 410082, Peoples R China
来源：
7TH WORLD MULTICONFERENCE ON SYSTEMICS, CYBERNETICS AND INFORMATICS, VOL XV, PROCEEDINGS: COMMUNICATION, CONTROL, SIGNAL AND OPTICS, TECHNOLOGIES AND APPLICATIONS | 2003年
关键词：
HAAR wavelet transform; neural network; Nonlinear analog; fault diagnosis; preprocessor;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, a fault diagnosis method based on wavelet and neural network for nonlinear analog circuit has been presented. The proposed method by using wavelet decomposition as a preprocessor of nonlinear analog circuit fault signal can drastically reduces the number of inputs and training and processing time of the neural network. After briefly introducing the basic principle based on HAAR wavelet and the neural network for fault diagnosis, the method of selecting the wavelet and fault feature is given.
引用
收藏
页码：331 / 335
页数：5
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