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Testing and Analysis of Induction Motor Electrical Faults Using Current Signature Analysis

机译:基于电流签名分析的感应电动机电气故障测试与分析

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摘要

The proposed method deals with the emerging technique called as Motor Current Signature Analysis (MCSA) to diagnosis the stator faults of Induction Motors. The performance of the proposed method deals with the emerging technique called as Motor Current Signature Analysis (MCSA) and the Zero-Sequence Voltage Component (ZSVC) to diagnose the stator faults of Induction Motors. The unalleviated study of the robustness of the industrial appliances is obligatory to verdict the fault of the machines at precipitate stages and thwart the machine from brutal damage. For all kinds of industry, a machine failure escorts to a diminution in production and cost increases. The Motor Current Signature Analysis (MCSA) is referred as the most predominant way to diagnose the faults of electrical machines. Since the detailed analysis of the current spectrum, the method will portray the typical fault state. This paper aims to present dissimilar stator faults which are classified under electrical faults using MCSA and the comparison of simulation and hardware results. The magnitude of these fault harmonics analyzes in detail by means of Finite-Element Method (FEM). The anticipated method can effectively perceive the trivial changes too during the operation of the motor and it shows in the results.
机译:所提出的方法涉及被称为电动机电流签名分析(MCSA)的新兴技术,用于诊断感应电动机的定子故障。该方法的性能涉及新兴技术,称为电动机电流签名分析(MCSA)和零序电压分量(ZSVC),以诊断感应电动机的定子故障。必须对工业设备的耐用性进行无懈可击的研究,才能判断出处于沉淀阶段的机器故障并阻止机器遭受残酷的破坏。对于所有行业,机器故障都会导致产量减少和成本增加。电动机电流签名分析(MCSA)被认为是诊断电机故障的最主要方法。由于对当前频谱进行了详细分析,因此该方法将描绘典型的故障状态。本文旨在介绍使用MCSA分类为电气故障的不同定子故障,并比较仿真结果和硬件结果。这些故障谐波的幅度通过有限元方法(FEM)进行详细分析。预期的方法也可以有效地感知电动机运行过程中的微小变化,并在结果中显示出来。

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