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Entropy-based broken rotor-bar fault detection and estimation of its severity in a three-phase induction motor

机译:基于熵的破损转子条故障检测和其在三相感应电动机中的严重程度的估计

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This paper presents detection of broken rotor bar fault using Stockwell transform of the stator current signals. The transform gives complex two-dimensional information pertaining to time and frequency. Entropy of the matrix with respect to time domain has been proposed as the fault detection parameter. Entropy is found to be useful for the detection as well as for the estimation of the severity of broken rotor bar faults. The results have been compared with the energy of the matrix. The results show that energy can only detect the fault unlike entropy. Thus, entropy can be used as a fault diagnostic parameter. The results have been validated on the experimentally recorded current signals for five different load conditions; from no-load to full-load.
机译:本文介绍了使用定子电流信号的泳盘变换的破损转子杆故障的检测。该变换使得与时间和频率有关的复杂的二维信息。已经提出了关于时域的矩阵的熵作为故障检测参数。发现熵对检测有用以及估计破碎的转子杆断层的严重程度。结果与基质的能量进行了比较。结果表明,能量只能检测到熵不同的故障。因此,熵可以用作故障诊断参数。结果已经在实验记录的电流信号上验证了五种不同的负载条件;从无加载到满载。

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