第二代小波变换在旋转机械故障诊断中的应用  

Application of Second Generation Wavelet Transform to Fault Diagnosis of Rotating Machinery

作　　者：段晨东[1] 李凌均[1] 何正嘉[1] 

机构地区：[1]西安交通大学机械工程学院

出　　处：《机械科学与技术》2004年第2期224-226,229,共4页Mechanical Science and Technology for Aerospace Engineering

基　　金：国家自然科学基金项目 (5 0 175 0 87);国家高技术研究发展计划专项经费项目 (2 0 0 1AA413 3 3 0 );"十五"国家科技攻关专项经费项目 (2 0 0 1BA2 0 413 0 5 )资助

摘　　要：不同类型的机械故障在振动信号中会反映出不同的波形特征 ,选用不适当的小波基函数会冲淡故障的特征信息 ,给故障诊断造成困难。第二代小波变换可以通过设计预测系数和提升系数获得具有某种特性的小波基函数。本文介绍了第二代小波变换的原理 ,研究了预测系数和提升系数与低通和高通滤波器系数之间的关系 ,根据信号的特征构造了基于插值细分方法的双正交小波 ,在旋转机械的轴系不对中故障诊断中取得了满意的效果。Different wave features for different machinery faults are reflected in vibration signal, but an improper wavelet basis function for vibration signal can blur the informationof fault features and make diagnosis difficult. In the second generation wavelet transform(SGWT), wavelet basis function with some special characteristiccan be obtained by means of designing prediction and update coefficients. In this paper, the principle of SGWT is described, and the relationship among the prediction coefficients, the update coefficients and the coefficients of low-pass and high-pass filter is discussed. According to the feature of a given signal, a biorthogonal wavelet is constructed which is based on interpolating subdivision scheme, good results are obtained for shaftingfault diagnosis in rotatingmachinery.

关 键 词：第二代小波变换 插值细分法 预测系数 提升系数 故障诊断 

分 类 号：TH17[机械工程—机械制造及自动化]