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Calculation of the electrical parameters for asynchronous motors under the periodically variable running condition

机译:周期性变化运行条件下异步电动机电气参数的计算

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The detection and diagnosis for the asynchronous motors' working states under the periodically variable running condition can be achieved by using theirs electrical parameters in the continuous short intervals, and the accuracy of these parameters can directly influence the results of the diagnosis. Fourier Transform has good properties and is a traditional method to exact the electrical parameters from the input signals. Unfortunately, it is easily corrupted by the presences of the frequency fluctuation and the noninteger harmonics in the signals. To overcome this defect of Fourier Transform, this paper presents a computational algorithm based on Complex Morlet Wavelet (CMW) to calculate the motors' electrical parameters, which has better time and frequency characteristics and increases the reliability and accuracy of the detection process. Simulations are conducted to verify the superiority of the proposed algorithm and the simulation results have shown that CMW algorithm is much more reliable and has much higher calculating accuracy than Fourier algorithm.
机译:通过在连续的短时间内使用异步电动机的电气参数,可以对异步电动机在周期性变化的运行状态下的工作状态进行检测和诊断,这些参数的准确性会直接影响诊断结果。傅里叶变换具有良好的性能,是一种从输入信号中精确提取电参数的传统方法。不幸的是,由于信号中存在频率波动和非整数谐波,很容易破坏它。为克服傅里叶变换的这一缺陷,提出了一种基于复Morlet小波(CMW)的计算算法,以计算电动机的电参数,具有更好的时间和频率特性,提高了检测过程的可靠性和准确性。通过仿真验证了所提算法的优越性,仿真结果表明,与傅立叶算法相比,CMW算法具有更高的可靠性和更高的计算精度。

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