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Separation harmonics for detecting broken bar fault in case of load torque oscillation

机译:分离谐波用于在负载扭矩振荡的情况下检测断条故障

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This paper presents separation harmonics to discriminate rotor failure from low frequency load torque oscillations in three phase induction motors. The most common method for detecting broken rotor bar faults is to analyze the corresponding sidebands through motor current signature analysis (MCSA). If a motor is subjected to load fluctuation, then the oscillation related sidebands exhibit similar behaviors as well. Particularly, when the load fluctuation frequency is close or equal to that of broken bars, the stator current spectrum analysis can be misleading. In this study, torque and motor phase voltage waveforms are exhaustively analyzed to discriminate broken rotor bar fault from low frequency load torque oscillation in three phase induction motors. In order to extract and justify the separation patterns, 2-D Time Stepping Finite Element Method (TSFEM) is used. The simulation and experimental results show that the proposed approach can successfully be applied to fault separation process in star connected motors.
机译:本文提出了分离谐波,以区分三相感应电动机中的转子故障与低频负载转矩振荡。检测转子条故障的最常见方法是通过电动机电流信号分析(MCSA)分析相应的边带。如果电动机承受负载波动,则与振荡相关的边带也会表现出类似的行为。特别是,当负载波动频率接近或等于断线的频率时,定子电流频谱分析可能会产生误导。在这项研究中,详尽地分析了转矩和电动机相电压波形,以从三相感应电动机的低频负载转矩振荡中识别出转子断条故障。为了提取和证明分离模式,使用了二维时间步进有限元方法(TSFEM)。仿真和实验结果表明,该方法可以成功地应用于星形电动机的故障分离过程。

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