宋向金, 赵文祥. 交流电机信号特征分析的滚动轴承故障诊断方法综述[J]. 中国电机工程学报, 2022, 42(4): 1582-1595. DOI: 10.13334/j.0258-8013.pcsee.210760
引用本文: 宋向金, 赵文祥. 交流电机信号特征分析的滚动轴承故障诊断方法综述[J]. 中国电机工程学报, 2022, 42(4): 1582-1595. DOI: 10.13334/j.0258-8013.pcsee.210760
SONG Xiangjin, ZHAO Wenxiang. A Review of Rolling Bearing Fault Diagnosis Approaches Using AC Motor Signature Analysis[J]. Proceedings of the CSEE, 2022, 42(4): 1582-1595. DOI: 10.13334/j.0258-8013.pcsee.210760
Citation: SONG Xiangjin, ZHAO Wenxiang. A Review of Rolling Bearing Fault Diagnosis Approaches Using AC Motor Signature Analysis[J]. Proceedings of the CSEE, 2022, 42(4): 1582-1595. DOI: 10.13334/j.0258-8013.pcsee.210760

交流电机信号特征分析的滚动轴承故障诊断方法综述

A Review of Rolling Bearing Fault Diagnosis Approaches Using AC Motor Signature Analysis

  • 摘要: 滚动轴承是保证交流电机正常运转的重要组成部件。相比于传统轴承故障诊断方法,电机电流和转速信号特征分析具有非侵入式且与控制系统共享信号的优势,逐渐被应用于交流电机轴承故障诊断领域。该文从理论模型和故障诊断两个方面,对相关领域的重要技术和前沿研究成果进行梳理归纳。对于故障诊断,主要介绍采用电机电流信号特征分析和电机转速信号特征分析的轴承故障诊断技术,同时指出各自的优缺点。最后,分析现有研究所面临的问题和挑战,并对未来发展趋势进行展望。

     

    Abstract: Rolling bearings are an important component to ensure the normal functioning of AC motors. Compared with traditional bearing fault diagnosis approaches, motor current and speed signature analysis has the advantages of non-intrusive and sharing signals with the control system, so it is gradually being applied in the field of the AC motor bearing fault diagnosis. In this survey paper, the important technologies and cutting-edge research results in the fields of theoretical model and fault diagnosis were summarized. For fault diagnosis, this paper mainly introduced the bearing fault diagnosis approaches using motor current signature analysis and motor speed signature analysis. At the same time, the advantages and disadvantages of these two bearing fault diagnosis techniques were pointed out. At last, the problems and challenges in present studies were discussed, and the future research directions are prospected.

     

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