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
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。
Abstract: 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.
文章引用：卞文慧, 王景玉. 转子–轴承故障多通道振动信号分析方法[J]. 建模与仿真, 2024, 13(1): 875-887. https://doi.org/10.12677/MOS.2024.131085

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