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基于小波包特征提取的模糊诊断网络建立及应用
引用本文:赵纪元,何正嘉.基于小波包特征提取的模糊诊断网络建立及应用[J].振动与冲击,1997,16(3):30-34.
作者姓名:赵纪元  何正嘉
作者单位:西安交通大学机械工程学院机自系 (赵纪元,何正嘉,孟庆丰),西安交通大学机械工程学院机自系(卢秉恒)
基金项目:国家自然科学基金资助项目.
摘    要:本文首先根据小波包分解原理和应用经验总结出小波包特征量与汽机故障对照表,将其与模糊综合评判和BP网络有机结合在一起,建立了基于小波包特征提取的模糊BP诊断网络模型.采用模糊综合评判技术,使该网络可在少量典型故障样本监督下训练成功,对于缺少机组运行故障知识库的厂家具有推广应用前景.最后举例说明,该网络在汽机诊断中是一种有效的智能分类器.

关 键 词:小波包  模糊综合评判  神经网络  故障诊断  振动信号

WAVELET PACKET FUZZY DIAGNOSIS NETWORK AND ITS APPLICATION
Zhao Jiyuan He Zhengjia Meng Qingfeng Lu Bingheng.WAVELET PACKET FUZZY DIAGNOSIS NETWORK AND ITS APPLICATION[J].Journal of Vibration and Shock,1997,16(3):30-34.
Authors:Zhao Jiyuan He Zhengjia Meng Qingfeng Lu Bingheng
Abstract:According to the principle of wavelet packets and its application experience, a correspondent table which embodies the relation between the turbogenerator faults and the features of wavelet packets is established and a new approach based on the table in tandem with fuzzy BP neural network is presented. Owing to employing fuzzy comprehension judgement, the network may be trained successfully with a few standard fault samples and applied in electrical power in-dustry which is short of standard fault samples. It is adopted to process and classify vibration signal of a turbogenerator and the results indicate that it is a useful and effective intelligential classification.
Keywords:wavelet packets  fuzzy comprehension judgement  neural network  fault diagnosis  vibration signal  
本文献已被 CNKI 维普 等数据库收录!
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