基于ⅡTD和包络信号1.5维谱的轴承故障诊断

摘要

In order to identify the early fault characteristics of bearing effectively,a bearing fault diagnosis method based on improved intrinsic time-scale decomposition (ⅡTD) and 1.5-dimensional spectrums of envelope signals was proposed.Endpoint extending is introduced to the traditional intrinsic time-scale decomposition (ⅠTD) method in order to improve its end effect,and the improved ⅠTD method is named as ⅡTD method.Bearing vibration signals were decomposed into a set of PR components and a trend term by the ⅡTD,and envelope signals of the PR components were analyzed by the 1.5-dimentional spectrum.The results demonstrated that the 1.5-dimentional spectrums of the PR component envelope signals obtained through the decomposition of the ⅡTD can accurately extract the shaft rotating frequency,the inner ring fault characteristic frequency and the outer ring fault characteristic frequency.Consequently,the bearing fault diagnosis was realized effectively,which proved the validity and practicability of the proposed method.%为了有效识别轴承的早期故障特征,提出了一种基于改进的本征时间尺度分解(ⅡTD)结合包络信号1.5维谱的轴承故障诊断方法.ⅡTD方法是将端点延拓引入到传统的本征时间尺度分解(ITD)当中,用于改善其端点效应.轴承振动信号经ⅡTD分解后得到一组PR分量和一趋势项,对PR分量的包络信号进行1.5维谱分析.结果表明,ⅡTD分解得到的PR分量包络信号的1.5维谱,可以准确提取轴的转动频率、内圈故障特征频率和外圈故障特征频率,从而实现了轴承故障的有效诊断,证明了该方法的有效性和实用性.