The influence study of wavelet properties on transient power disturbance signals detection

Wavelet transform is widely used in the transient disturbance signals detection. However, wavelet properties have great impact on detection results. If wavelet choice is improper, it will lead to failures in disturbances detection. Based on analyzing the cancellation, support set, smoothness and other properties of wavelet, make detection for different disturbances by using wavelet modulus maxima principles. The view that the wavelet with higher cancellation, longer support length and better smoothness should be chosen in transient power quality disturbance signals detection is first proposed in this paper. Select four typical wavelets, i.e. Haar, Symlet8, DB2, DB10 wavelet to make detection for voltage sag and oscillatory transient disturbances. Experimental results show that selection principles proposed in this paper is correct and reliable.