Power Quality Disturbance Detection and Classification Using Chirplet Transforms
In this paper, a new approach is presented for the detection and classification of PQ disturbance in power system by Chirplet transforms(CT), which is the generalized forms of Fourier transform(FT), short-time Fourier transform(STFT) and wavelet transform(WT). WT and wavelet ridge are very useful tools to analyze PQ disturbance signals, but invalid for nonlinear time-varying harmonic signals. CT can detect and identify voltage quality and frequency quality visually, i.e., according to the contour of CT matrix of PQ harmonic signals, the harmonics can be detect and identify to fixed, linear time-varying and nonlinear time-varying visually. It is helpful to choose appropriate WT to analyze harmonics. Simulations show the contours of CT can effectively detect harmonic disturbance occurrence time and duration. Finally, it is validated that the harmonics of the stator current fault signal of the bar-broken electric machine is nonlinear time-varying, and tend to stable status in a short time.
KeywordsWavelet Transform Wavelet Packet Harmonic Signal Power Quality Voltage Interruption
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