旋转机械故障诊断中的振动信号模型综述

Vibration Signal Models in Rotating Machinery Fault Diagnosis:A Review

对旋转机械振动信号进行信号处理,能够有效提取特征进行故障诊断。振动信号模型来自旋转机械运动学和动力学机理,以数学形式表达,可以指导信号处理方法的设计。随着故障机理研究和信号处理方法研究的推进,研究人员对信号模型进行了发展,并基于这些信号模型设计了相应的信号处理方法。首先,介绍了一般化的信号模型,包括周期信号模型、循环平稳信号模型、自适应谐波模型、波形函数模型、任意阶谐波模型等,以及对应的信号处理方法;其次,分别介绍定工况和变工况条件下针对轴承和齿轮的典型振动信号模型及对应信号处理方法;最后,对振动信号模型的研究发展进行总结和展望,旨在回顾旋转机械故障诊断所涉及的信号模型,并说明其在信号处理算法设计和故障诊断特征提取中的价值和意义。

Analyzing vibration signals from rotating machinery can effectively extract features to diagnose equipment health conditions.Vibration signal models are derived from the kinematics and dynamics of rotating machinery,expressed in mathematical form,and can guide the design of signal processing methods.With advancements in the research of fault mechanism and signal processing,researchers have developed an increasing num-ber of signal models,and designed corresponding signal processing methods based on these models.We first introduce generalized signal models,including the periodic signal model,the cyclo-stationary signal model,the adaptive harmonic model,the wave-shape model,and the arbitrary order harmonic model,etc.,and their corresponding signal processing methods;then,typical vibration signal models for bearings and gears under constant and time-varying operating conditions are discussed,along with their respective signal processing methods;finally,conclusions and outlooks of the research development of vibration signal models are given.We aim to review signal models involved in rotating machinery fault diagnosis and to highlight their significance in designing methods for signal processing and feature extraction.