转子–轴承故障多通道振动信号分析方法  

Multi-Channel Vibration Signal Analysis Method for Rotor-Bearing Faults

作　　者：卞文慧 王景玉 

机构地区：[1]上海理工大学机械工程学院,上海 [2]南昌工程学院信息工程学院,江西 南昌

出　　处：《建模与仿真》2024年第1期875-887,共13页Modeling and Simulation

摘　　要：本文基于Rehman等于2011年提出的多元经验模态分解算法(Multivariate Empirical Mode Decom-position, MEMD)开展研究。该算法是经验模态分解(Empirical Mode Decomposition, EMD)用于多通道数据方面的应用,通过结合MEMD的基本理论,提出了多通道振动信号分析方法,首先,采集多通道振动信号,然后利用MEMD对多通道振动信号进行自适应分解,得到一系列多元本征模态函数(Intrinsic Mode Function, IMF)分量;接着,依据峭度准则从中选取包含故障信息的IMF分量;最后,对选出的分量采用频谱分析和Hilbert包络分析,提取故障特征。This paper carried out research based on the Multivariate Empirical Mode Decomposition (MEMD) algorithm proposed by Rehman in 2011. The algorithm is an Empirical Mode Decomposition (EMD) applied to multi-channel data. Combining the basic theory of MEMD, a multi-channel vibration sig-nal analysis method is proposed. First, multi-channel vibration signals are collected. Then a series of Intrinsic Mode Function (IMF) components are obtained by the adaptive decomposition of mul-ti-channel vibration signals using MEMD. Then, IMF components containing fault information are selected according to the Kurtosis criterion. Finally, spectrum analysis and Hilbert envelope analy-sis are used to extract fault characteristics.

关 键 词：多元经验模态分解 多通道振动信号分析 故障诊断 滚动轴承 峭度准则 信号仿真 

分 类 号：TN9[电子电信—信息与通信工程]