基于振动信号融合分析的电机偏心故障诊断

Fault Diagnosis of Motor Eccentricity Based on Vibration Signal Fusion Analysis

为提高异步电机气隙偏心故障诊断的可靠性,提出一种基于振动信号融合分析的异步电机气隙偏心故障诊断方法。首先,采集不同偏心故障类型下的径向电磁力和不平衡磁拉力信号;其次,对信号进行融合相关分析,建立不同信号间的相关关系;最后,通过振动信号融合相关谱图可判断电机是否存在偏心故障及偏心故障的类型。该方法通过对故障特征信号的融合相关分析,能够突出故障特征频率分量,降低故障识别难度。通过仿真分析,验证了该方法的有效性和实用性,对于电机运行状态的准确监测具有重要意义。

Aiming to improve the reliability of the fault diagnosis of induction motor air gap eccentricity,this paper proposed a fault diagnosis method of induction motor air-gap eccentricity based on vibration signal fusion analysis.Firstly,the radial electromagnetic force and unbalanced magnetic pull signals under different types of eccentricity fault are collected.Then,the fusion correlation analysis of the signals is carried out to establish the correlation between different signals.Lastly,the eccentricity fault and the type of eccentricity fault can be judged by the vibration signal fusion correlation spectrum.Through the fusion correlation analysis of fault characteristic signals,this method can highlight the fault characteristic frequency components and reduce the difficulty of fault identification.Through simulation analysis,the effectiveness and practicability of the method are verified,and it is of great significance for the accurate monitoring of the motor running state.