经验模态分解与阶次跟踪分析对机器人用精密减速器故障诊断  

Empirical Mode Decomposition and Order Tracking Analysis of Fault Diagnosis of Robot with Precision Reducer

作　　者：蔺梦雄 张文松 曹洪鑫 张向慧 姚良博 张敬彩[2] LIN Mengxiong;ZHANG Wensong;CAO Hongxin;ZHANG Xianghui;YAO Liangbo;ZHANG Jingcai(School of Mechanical and Material Engineering,North China University of Technology,Beijing 100144,China;China Productivity Center for Machinery Co.,Ltd.,Beijing 100044,China)

机构地区：[1]北方工业大学机械与材料工程学院,北京100144 [2]中机生产力促进中心有限公司,北京100044

出　　处：《机械科学与技术》2024年第6期943-949,共7页Mechanical Science and Technology for Aerospace Engineering

摘　　要：针对行星摆线针轮减速器的故障特征在摆动疲劳实验中难以提取的问题,本文提出了一种经验模态分解(Empirical mode decomposition,EMD)与阶次跟踪分析结合的方法对疲劳实验中的减速器进行故障诊断。通过对采集到的时域信号进行等角域重采样、经验模态分解、计算固有模态分量(Intrinsic mode function,IMF)的峭度值、选取固有模态分量重构、快速傅里叶变换(Fast fourier transform,FFT)后得到阶次图进行验证。结果表明:该方法能够准确的提取包含故障信息的固有模态分量,实现了行星摆线针轮减速器在非平稳状态下的故障特征识别。Because the fault features of a planetary cycloid pinwheel reducer are difficult to extract in the swing fatigue experiment,this paper proposes a method that combines empirical mode decomposition and order tracking analysis to conduct the fault diagnosis of the reducer.Through performing equiangular domain resampling,empirical mode decomposition,calculating the kurtosis value of the intrinsic mode function,selecting the intrinsic mode component for reconstruction and the fast Fourier transform of collected time domain signals,the order map is verified.The results show that the method can accurately extract the inherent modal components that contain the information on faults and identify the fault features of the planetary cycloid pinwheel reducer in the non-stationary state.

关 键 词：行星摆线针轮减速器 经验模态分解 阶次分析 故障诊断 

分 类 号：TH16[机械工程—机械制造及自动化]