摘要
针对目前滚动轴承中多种微弱故障难以准确识别的难题,提出基于高密度离散小波变换和包络谱的滚动轴承复合故障诊断方法。首先对采集的轴承振动信号进行高密度离散小波变换;然后对各尺度上的小波系数和尺度系数进行单子带重构,以消除频率混叠的影响;最后对各子带信号分量进行包络谱分析,并通过滚动轴承各典型故障的特征频率,识别滚动轴承存在的各种故障。将所提方法应用于具有复合故障的滚动轴承的诊断,并与其他常用的诊断方法进行对比,结果表明该方法能有效地实现滚动轴承早期复合故障诊断。
Aiming at the difficulties in accurate reorganization of several weak faults currently,a composite fault diagnosis method based on higher density discrete wavelet transform and envelope spectrum is proposed.Firstly,the higher density discrete wavelet transform is used to decompose acquired vibration signals of rolling bearings.Then,the single-subband reconstruction is performed on the wavelet coefficients and scaling coefficients at each scale in order to solve frequency aliasing.Finally,the envelope spectra of all subband signals are calculated,and all faults can be recognized according to the characteristic frequencies of the typical faults.The proposed method is applied to the diagnosis of the rolling bearings with composite faults,and is compared with other common fault diagnosis method.The results show that the proposed method can be effectively used for the early composite fault diagnosis of rolling bearings.
出处
《重庆大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2013年第3期13-19,共7页
Journal of Chongqing University
基金
国家自然科学基金资助项目(50905191
51005262)
重庆市科委自然科学基金计划资助项目(2010BB4227)
关键词
小波变换
滚动轴承
故障诊断
单子带重构
包络谱
wavelet transforms
rolling bearing
fault diagnosis
single-subband reconstruction
envelope spectrum
