机械科学与技术2012，Vol.31Issue(7)：1201-1204,4.
正交小波变换支持向量数据描述在轴承性能评估中的应用
Applying Orthogonal Wavelet Transform-SVDD to Evaluating Performance of Bearing
摘要
Abstract
The support vector data description （SVDD） is a kind of single-value classification method, by which a single-value classifier can be built by using its normal state data samples even if the fault samples are lacking, thus revealing its normal operation. The orthogonal wavelet transform （OWT） has good performance for extracting the shock elements of a non-stable signal. We propose a new state evaluation method that uses the SVDD and the OWT and use the OWT to extract the peak-peak values of various detail signals, which are in turn used as input parame- ters of the classifier. We build the classification model of the classifier with the SVDD method to carry out the quan- titive evaluation of the state of the machine. We also use our method to do experimental analysis of the pitting faults on the inner ring of a rolling bearing and establish the quantitive indicators for evaluating its worsening perform- ance; the experimental results show that our method is effective.关键词
支持向量数据描述/故障诊断/性能评估/正交小波变换Key words
support vector data description(SVDD)/fault diagnosis/performance evaluation/orthogonalwavelet transform分类
机械制造引用本文复制引用
李凌均,韩捷,李卫鹏,郝伟..正交小波变换支持向量数据描述在轴承性能评估中的应用[J].机械科学与技术,2012,31(7):1201-1204,4.基金项目
国家自然科学基金项目（50675209）,河南省自然科学基金项目（0611022400）和河南省杰出人才创新基金项目（0621000500）资助 （）
