滚动轴承振动信号的多重分形特性分析  

Multifractal Characteristic Analysis on Vibration Signal of Rolling Bearings

作　　者：陈龙[1] 邵梦博 孟相旭 刘红彬[1] CHEN Long;SHAO Mengbo;MENG Xiangxu;LIU Hongbin(School of Mechatronics Engineering, Henan University of Science and Technology, Luoyang 471003, China;School of Mechanical Engineering and Automation,Beihang University,Beijing 100191,China;Shandong Yongxiang Special Bearing Co., Ltd.,Liaocheng 252000,China)

机构地区：[1]河南科技大学机电工程学院,河南洛阳471003 [2]北京航空航天大学机械工程及自动化学院,北京100191 [3]山东永翔特种轴承有限公司,山东聊城252000

出　　处：《轴承》2020年第9期43-49,56,共8页Bearing

基　　金：河南科技大学博士科研启动基金(13480075);中国智能制造新模式应用项目(2017ZNZX04)。

摘　　要：针对多重分形方法具备自相似特性并能发掘时间序列内部演变结构的特点,开展了多种轴承振动信号的多重分形特征研究,研究结果表明:轴承振动信号具备多重分形特性且该特性受时间序列的长相关性与胖尾分布的共同影响,研究结果为轴承振动性能变异的过程预测提供了新的理论基础,为滚动轴承应用中的性能预测开辟了新的途径。In view of the fact that the multifractal method has self similarity and can discover internal evolution structure of time series,the multifractal characteristics are studied for vibration signal of various bearings.The research results show that the vibration of the bearings has multifractal characteristics,which are affected by long-term correlation of time series and fat-tailed distribution.The research results provide a new theoretical basis for process prediction of vibration performance variation of the bearings,and open a new way for performance prediction in application of rolling bearings.

关 键 词：滚动轴承 振动 多重分形 性能指标 胖尾分布 

分 类 号：TH133.33[机械工程—机械制造及自动化] TB53[理学—物理]