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A wavelet-based technique for discrimination between faults and magnetizing inrush currents in transformers

机译:基于小波的变压器故障和励磁涌流判别技术

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This paper presents the development of a wavelet-based scheme, for distinguishing between transformer inrush currents and power system fault currents, which proved to provide a reliable, fast, and computationally efficient tool. The operating time of the scheme is less than half the power frequency cycle (based on a 5-kHz sampling rate). In this work, a wavelet transform concept is presented. Feature extraction and method of discrimination between transformer inrush and fault currents is derived. A 132/11-kV transformer connected to a 132-kV power system were simulated using the EMTP. The generated data were used by the MATLAB to test the performance of the technique as to its speed of response, computational burden and reliability. The proposed scheme proved to be reliable, accurate, and fast.
机译:本文提出了一种基于小波的方案,以区分变压器的涌入电流和电力系统的故障电流,事实证明该方法可提供可靠,快速且计算高效的工具。该方案的工作时间少于电源频率周期的一半(基于5 kHz采样率)。在这项工作中,提出了一个小波变换概念。推导了变压器涌流与故障电流的特征提取及判别方法。使用EMTP对连接到132 kV电力系统的132/11 kV变压器进行了仿真。 MATLAB将生成的数据用于测试该技术在响应速度,计算负担和可靠性方面的性能。所提出的方案被证明是可靠,准确和快速的。

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