Fault severity diagnosis of squirrel-cage induction motors in transient regime based on curve fitting

X. Xiao, Li Chai, Yuxia Sheng
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引用次数: 1

Abstract

Many motor current signature analysis (MCSA) methods have been proposed for the rotor fault diagnosis of induction motor. However, few method provides the quantitative measurement. In this paper, a method is proposed to diagnose rotor fault severity based on the transient current. First, wavelet transform is used to analyze the stator current and detect rotor bars. Then, a curve fitting algorithm is proposed to diagnose the asymmetric rotor condition and give the precaution value and alarm value. Lastly, a fault severity factor is presented based on the two aforementioned values. The proposed method is demonstrated by simulation experiment, which shows that it can give the evaluation of rotor asymmetry and fault severity.
基于曲线拟合的鼠笼型异步电动机暂态故障严重程度诊断
针对异步电动机转子故障诊断,提出了多种电机电流特征分析方法。然而,很少有方法提供定量测量。本文提出了一种基于暂态电流的转子故障严重程度诊断方法。首先,利用小波变换分析定子电流,检测转子棒;然后,提出了一种曲线拟合算法来诊断转子不对称状态,并给出了预警值和报警值。最后,基于上述两个值提出了故障严重程度因子。通过仿真实验验证了该方法的有效性,结果表明该方法能够对转子不对称性和故障严重程度进行评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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