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小波包和SVM在发动机故障诊断中的应用
引用本文:范红波,张英堂,孙烨. 小波包和SVM在发动机故障诊断中的应用[J]. 车用发动机, 2006, 0(4): 49-53
作者姓名:范红波  张英堂  孙烨
作者单位:军械工程学院,河北,石家庄,050003;武汉军械士官学校,湖北,武汉,430075
摘    要:针对发动机的故障特点,提出了一种基于小波包和支持向量机(SVM)的发动机故障诊断方法。利用信号能量在小波包空间的分布特性,采用基于能量的自适应去噪方法,提取反映故障的特征向量,并基于SVM理论构建了针对发动机的多故障分类器。试验结果表明,该方法具有故障分类与识别能力。

关 键 词:小波包  SVM  内燃机  故障诊断
文章编号:1001-2222(2006)04-0049-05
收稿时间:2006-03-02
修稿时间:2006-07-12

Application of Wavelet Packet and Support Vector Machines in the Engine Fault Diagnosis
FAN Hong-bo,ZHANG Ying-tang,SUN Ye. Application of Wavelet Packet and Support Vector Machines in the Engine Fault Diagnosis[J]. Vehicle Engine, 2006, 0(4): 49-53
Authors:FAN Hong-bo  ZHANG Ying-tang  SUN Ye
Affiliation:1. Ordnance Engineering College, Shijiazhuartg 050003, China; 2.Wuhan Ordnance N. C. O Academy of PLA, Wuhan 430075, China
Abstract:In this paper,a method of engine fault diagnosis is put forward based on wavelet packet and support vector machines(SVM).By means of the distribution characteristic of signal energy in the wavelet packet space and the method of self adapting denoise,eigenvectors are extracted.Then,multi-fault classifier is constructed for engine based on SVM theory.The classification and recognition capability of the classifier is proved by the results of experimentation.
Keywords:wavelet packet  SVM  ICE  fault diagnosis
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