| 小波包在故障诊断中的应用 |
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| 引用本文： | 王荣杰,胡清. 小波包在故障诊断中的应用[J]. 微计算机信息, 2006, 22(28): 232-234 |
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| 作者姓名： | 王荣杰 胡清 |
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| 作者单位： | 510006,广州广东工业大学信息工程学院 |
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| 摘 要： | 主要研究小波包变换和神经网络相结合的故障诊断技术。首先利用小波包的多分辨率分析的特点,对故障信号进行多尺度的分解,正交和归一化处理后,根据主成份分析原理提取故障特征向量作为神经网络的训练样本,设计故障类型识别器。仿真结果证实了该方法的有效性和可行性。
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| 关 键 词： | 故障诊断 小波包 主成分分析 BP网络 |
| 文章编号： | 1008-0570(2006)10-1-0232-03 |
| 修稿时间： | 2006-02-07 |
Application of Wavelet Packet in Fault Diagnosis |
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| Wang,Rongjie,Hu,Qing. Application of Wavelet Packet in Fault Diagnosis[J]. Control & Automation, 2006, 22(28): 232-234 |
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| Authors: | Wang Rongjie Hu Qing |
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| Abstract: | Research on the fault diagnose based on the combination of wavelet packet transformation and neural network mainly.By using the character of wavelet packet multiresolution,fault signal is decomposed at multi-scale,orthogonalation and normalization,extract feature vector according to principal component analysis theory,which as training input of neural network,design classifier of fault pattern.The validity and feasibility of the fault diagnosis method is demonstrated by a simulation. |
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| Keywords: | Fault diagnosis Wavelet packet Principal component analysis Back propagation neural network |
| 本文献已被 CNKI 万方数据 等数据库收录！ |
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