| 一种基于小波和人工神经网络的故障检测与诊断方法 |
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| 引用本文： | 胡昌华,张军波,李学锋.一种基于小波和人工神经网络的故障检测与诊断方法[J].航天控制,2000,18(2):64-71. |
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| 作者姓名： | 胡昌华 张军波 李学锋 |
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| 作者单位： | Hu Changhua
,Zhang Junbo
(Section 302, The Second Artillery Engineering College, Xi’an, 710025)Li Xuefeng
(Beijing Aerospace Automatic Control Institute, Beijing 100854) |
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| 摘 要： | 提出了一种基于小波和人工神经网络的故障检测与诊断的方法，该方法利用小波包分解的精确细分的特点，分别对正常系统和故障系统的采样信号进行精确特征提取，并构造一系列基于信号能量且具有表征系统状态能力的特征向量，然后利用人工神经网络分类器对系统在各种状态下的特征向量进行分类决策，从而实现对系统的故障检测与诊断。
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| 关 键 词： | 人工神经元网络 故障诊测 故障诊断 |
| 修稿时间： | 2000-01-13 |
A Method of Fault Detection and Diagnosis Based on Wavelet and Artificial Neural Networks |
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| Hu Changhua
,Zhang Junbo
Li Xuefeng.A Method of Fault Detection and Diagnosis Based on Wavelet and Artificial Neural Networks[J].Aerospace Control,2000,18(2):64-71. |
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| Authors: | Hu Changhua Zhang Junbo
Li Xuefeng |
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| Abstract: | A method of fault detection and diagnosis based on wavelet and artificial neural networks is proposed in this paper. The eigen-vectors of the normal system and fault system are extracted by virtue of precise subdivision of wavelet packet decomposition, and a series of eigen-vectors based on signal energy are constructed. Then eigen-vector under a certain state can be assorted and decided by use of artificial neural networks sorter and realize fault detection and diagnosis to the system sequentially. |
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| Keywords: | Artificial neural network Fault detection Fault diagnosis |
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