基于电流和振动特征分析的三相感应电动机健康监测

Muhammad Sarfraz Moiz, Shazaib Shamim, M. Abdullah, Hamdan Khan, I. Hussain, Anas Bin Iftikhar, T. Memon
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引用次数: 12

摘要

本文主要讨论了采用电流特征分析和振动特征分析两种重要的方法来检测三相异步电动机的故障,特别是外滚道轴承故障,以部署预测性维护技术。轴承故障的检测非常重要,因为感应电机的大多数故障都与轴承故障有关,而轴承故障会导致过多的停机时间和巨大的收入损失。及早发现故障有助于减少停机时间和意外故障。电流特征分析使用定子电流谱来确定基频附近的故障谐波。每台机器都会产生振动,由于动应力的存在,机器的振动行为受到机械条件的影响。这种扰动可以通过振动特征分析进行分析。实验在1 HP感应电动机上进行,连接三相50 Hz电源,人为损坏6303型轴承以产生故障条件。从实验结果中,我们比较了上述两种故障检测技术,并分析了轴承故障频率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Health Monitoring of Three-Phase Induction Motor Using Current and Vibration Signature Analysis
This paper revolves around the discussion of detection of faults occurs in three-phase induction motor especially outer-race bearing faults using two significant methods, Current Signature Analysis and Vibration Signature Analysis, in order to deploy predictive maintenance technique. Detection of bearing fault is important because most of the failures in induction motors are related to bearing faults which can lead to excessive downtimes and large revenue losses. Early detection of fault helps to reduce downtime and unexpected breakdowns. The current signature analysis uses stator currents spectrum to determine fault harmonics around the fundamental frequency. Every machine generates vibration and due to dynamic stresses, vibrational behavior of the machine is influenced by the mechanical condition. This disturbance can be analyzed by Vibration signature analysis. The experiment is done on induction motor of 1 HP, connected to three-phase 50 Hz supply and 6303 model bearings are artificially damaged to generate fault conditions. From experimental results, we have compared the above two techniques for fault detection and analyze the bearing fault frequency.
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