摘要
针对强背景噪声下滚动轴承振动信号故障特征信息难以提取的问题,提出了结合固有时间尺度分解(ITD)-形态滤波和Teager能量谱的滚动轴承故障特征提取与诊断方法。首先对滚动轴承振动信号采用ITD方法分解,得到若干个固有旋转分量;考虑到噪声主要分布在高频段,取前2个高频的固有旋转分量进行形态滤波,并将滤波后的信号与剩余固有旋转分量重构;对重构信号计算Teager能量算子并绘制Teager能量谱,从Teager能量谱中可以识别出故障特征。将本方法应用于滚动轴承的内圈故障和外圈故障诊断,结果表明ITD-形态滤波可以有效去除振动信号中的背景噪声并保留冲击特征,Teager能量谱可以直观并准确显示出故障特征。
The fault features of rolling bearing vibration signal usually are immersed in heavy background noise and difficult to be extracted. Aiming at this problem, a fault feature extraction and diagnosis method for rolling bearing is proposed based on the combination of intrinsic time scale decomposition （ITD）-morphological filter and Teager energy spectrum. The original vibration signal of rolling bearing is decomposed into several proper rotation （PR） components with ITD method. The morphological filter is performed on the first two PR components to reduce the noises considering that the noises are mainly distributed on the high frequency band. The filtered signal and the other PR components are reconstructed as a new target signal to extract fault features. The Teager energy operator of the reconstructed signal is calculated and the Teager energy spectrum is obtained with FFT. The fault features could be identified from the Teager energy spectrum. The proposed method was applied to the fault diagnosis of the defective rolling bearings with inner race fault and outer race fault. The results indicate that the ITD-morphological fiher method could effectively eliminate the background noise in the vibration signal and reserve the impulse features of the hearing signal. The Teager energy spectrum could reveal the fault features explicitly and accurately.
出处
《仪器仪表学报》
EI
CAS
CSCD
北大核心
2016年第4期788-795,共8页
Chinese Journal of Scientific Instrument
基金
国家科技支撑计划课题(2014BAF08B05)
国家自然科学基金(51205292)项目资助
关键词
滚动轴承
故障诊断
固有时间尺度分解
形态滤波
Teager能量谱
rolling bearing
fault diagnosis
intrinsic time scale decomposition （ITD）
morphological filter
Teager energy spectrum
