摘要
针对非平稳工况下,轴承故障信号表现出来的非平稳性、故障特征难以提取等特点,提出将阶次分析与经验小波变换(EWT)相结合的故障特征提取方法,使用Lab VIEW软件开发平台对上述方法进行编程实现。利用机械故障仿真实验台(MFS)得到非平稳工况下轴承内圈故障信号并以其进行分析,分析结果表明:基于阶次分析与EWT相结合的方法能准确识别非平稳工况下轴承故障特征,解决了传统阶次分析方法无法有效识别故障特征的问题。
For non-stationary conditions,bearing fault signal manifested non-stationary,it is difficult to fault feature extraction,etc.,is proposed where in the fault order analysis and empirical wavelet transform(EWT)a combination of extraction methods,using LabVIEW software development platform to program the above method.The mechanical fault simulation experiment platform(MFS)was used to get the bearing inner ring fault signal under non-steady condition and analyze it.The results show that:The method based on the combination of order analysis and EWT can accurately identify the bearing fault characteristics under non-stationary conditions,solve the traditional order analysis method can not effectively identify the characteristics of the fault.
作者
颜丙生
聂士杰
汤宝平
刘自然
YAN Bing-sheng;NIE Shi-jie;TANG Bao-ping;LIU Zi-ran(College of Mechanical and Electrical Engineering,Henan University of Technology,Zhengzhou 450007,China)
出处
《组合机床与自动化加工技术》
北大核心
2018年第7期51-54,共4页
Modular Machine Tool & Automatic Manufacturing Technique
基金
国家自然科学基金项目资助(U1604134)
河南工业大学科教融合项目资助(26400038)
河南省高等学校重点科研计划项目资助(19A460014)
关键词
故障诊断
阶次分析
经验小波变换
包络谱分析
fault diagnosis
order analysis
experience wavelet transform
envelope analysis
