电动机轴承故障诊断的循环平稳方法  

Cyclostationary Analysis of Diagnose Motor Bearing Fault

作　　者：王小卉[1] 杨洁明[2] 

机构地区：[1]湛江师范学院机电工程系,广东湛江524048 [2]太原理工大学机电研究所,山西太原030024

出　　处：《新技术新工艺》2012年第8期84-87,共4页New Technology & New Process

基　　金：国家自然基金资助项目(5097188);湛江师范学院自然科学研究青年项目(QL1005)

摘　　要：通过信号仿真,研究了二阶循环平稳分析的解调性能,并总结出循环自相关与谱相关切片函数的一般规律,分析了故障电动机轴承振动信号的循环平稳特性。试验中,模拟并采集工况中带有强噪声的内圈故障电动机轴承的振动信号,提出用小波消噪与特殊频率处谱相关切片结合的分析方法,进行特征提取,分析过程中发现,这种方法能有效实现轴承快速诊断,避免三维函数分析信息冗余、计算量庞大的缺点,同时也排除了瞬时转速与额定转速偏差引起的干扰。In this paper, we Studied the demodulation performance of second-order cyelostationary by signal simulation, summed up the general laws of slice spectrum for cyclic autocorrelation function （CAF） and spectrum correlation density function （SCDF）, and studied the cyelostationary features of fault motor bearing vibration signal. In the Experiment, we simulated and collected the vibration signals of motor bearing which has inner ring pitting with strong noise, then proposed wavelet and slice spectrum analysis of SCDF methods, the analysis found that this method can diagnose bearing fault rapid- ly, to avoid the information redundancy and large volume of the three-dimensional function analysis with this method, we can rule out the possibility of interference caused by the deviation of instantaneous speed and rated speed.

关 键 词：电机轴承 故障诊断 循环平稳 

分 类 号：TH133.3[机械工程—机械制造及自动化]