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

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.