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首页> 外文期刊>IEEE Transactions on Energy Conversion >Condition Monitoring and Fault Diagnosis of Electrical Motors - A Review
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Condition Monitoring and Fault Diagnosis of Electrical Motors - A Review

机译：电动机状态监测与故障诊断研究述评

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摘要

Recently, research has picked up a fervent pace in the area of fault diagnosis of electrical machines. The manufacturers and users of these drives are now keen to include diagnostic features in the software to improve salability and reliability. Apart from locating specific harmonic components in the line current (popularly known as motor current signature analysis), other signals, such as speed, torque, noise, vibration etc., are also explored for their frequency contents. Sometimes, altogether different techniques, such as thermal measurements, chemical analysis, etc., are also employed to find out the nature and the degree of the fault. In addition, human involvement in the actual fault detection decision making is slowly being replaced by automated tools, such as expert systems, neural networks, fuzzy-logic-based systems; to name a few. It is indeed evident that this area is vast in scope. Hence, keeping in mind the need for future research, a review paper describing different types of faults and the signatures they generate and their diagnostics' schemes will not be entirely out of place. In particular, such a review helps to avoid repetition of past work and gives a bird's eye view to a new researcher in this area.
机译：最近，在电机故障诊断领域的研究取得了飞跃的发展。这些驱动器的制造商和用户现在渴望在软件中包含诊断功能，以提高可销售性和可靠性。除了在线路电流中定位特定的谐波分量（通常称为电动机电流信号分析）之外，还探究了其他信号（例如速度，转矩，噪声，振动等）的频率内容。有时，也可以采用完全不同的技术（例如热测量，化学分析等）来找出故障的性质和程度。此外，人类参与实际故障检测决策的过程正逐渐被自动化工具所取代，例如专家系统，神经网络，基于模糊逻辑的系统；仅举几例。显然，这一领域的范围很广。因此，考虑到对未来研究的需求，描述不同类型的故障及其产生的特征以及诊断方案的评论文件不会完全消失。尤其是，这样的审查有助于避免重复过去的工作，并使这一领域的新研究人员鸟瞰。

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