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A case study of bearing fault monitoring techniques for induction motors

机译:异步电动机轴承故障监测技术的案例研究

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摘要

Research has witnessed considerable advancement in the field of fault detection and monitoring in induction motors. The advent of on-line and automated systems for fault diagnosis has added a new dimension in the area of condition monitoring of induction motors. So keeping in mind the vast scope of this field of research and the economic impact that bearing failures have on industries, a review of different techniques used for bearing fault detection is done by compiling various available literatures.In this paper the different bearing fault detection methodologies are grouped according to the techniques used for bearing fault detection. The advantages and disadvantages associated with the fault detection schemes are also reported. The review illustrates that bearing fault detection is primarily done using Fourier transform based analysis and/or Wavelet transform based tools by analyzing vibration signals and/or motor current signals. The vibration signals have proved to be the superior option pertaining to the various advantages as discussed in the literature. The objective of the present work is to unfold a broad area of the updated status of the bearing fault monitoring and will assist future researchers to realize the scope of research in this area at a glimpse.
机译:研究已经见证了感应电动机故障检测和监视领域的巨大进步。用于故障诊断的在线和自动化系统的出现在感应电动机的状态监测领域中增加了新的领域。因此,考虑到该研究领域的广泛范围以及轴承故障对行业的经济影响,通过汇编各种可用文献对轴承故障检测所使用的不同技术进行了综述。根据用于轴承故障检测的技术进行分组。还报告了与故障检测方案相关的优缺点。该评论表明,轴承故障检测主要是通过分析振动信号和/或电动机电流信号使用基于傅立叶变换的分析和/或基于小波变换的工具完成的。事实证明,振动信号是具有多种优势的最佳选择,如文献所述。当前工作的目的是展开轴承故障监控的最新状态的广阔领域,并将帮助未来的研究人员快速了解这一领域的研究范围。

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