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

机译:基于曲线拟合的暂态鼠笼式异步电动机故障严重性诊断

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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.
机译:已经提出了许多用于感应电动机的转子故障诊断的电动机电流签名分析(MCSA)方法。但是,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性诊断方法。首先,小波变换用于分析定子电流并检测转子棒。然后,提出了一种曲线拟合算法,对转子的不对称状态进行诊断,给出预警值和报警值。最后,基于上述两个值给出了故障严重性因子。仿真实验证明了该方法的有效性,表明该方法可以对转子的不对称性和故障严重程度进行评估。

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