Fault diagnosis using wavelet neural networks

被引：0

作者：

Liu, QP ^{[1
]}

Yu, XL ^{[1
]}

Feng, QK ^{[1
]}

机构：

[1] Xian Jiaotong Univ, Sch Energy & Power Engn, Xian 710049, Shanxi, Peoples R China

来源：

NEURAL PROCESSING LETTERS | 2003年 / 18卷 / 02期

关键词：

fault diagnosis; feature extraction; neural networks; RBF; wavelet neural networks; WBF;

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：

Wavelet neural networks are a class of neural networks consisting of wavelets. This paper presents a novel universal tool for fault diagnosis and algorithms for wavelet neural network construction are proposed. Using the model of wavelet neural networks, we can not only extract the features of system but also predict the development of the fault.

引用

页码：115 / 123

页数：9

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