Enhanced Detection of Power-Quality Events Using Intra and Interscale Dependencies of Wavelet Coefficients

Noise in power-quality (PQ) signals has been the biggest hurdle in wavelet-based detection and time localization of PQ events. The well-known threshold-based denoising techniques, used in the signal-processing area, do not perform well with practical PQ waveform data. This paper proposes a simple yet effective denoising technique using inter and intrascale dependencies of wavelet coefficients to denoise PQ waveform data for enhanced detection and time localization of PQ disturbances. Utilizing the fact that the wavelet coefficients are not only correlated with its local neighborhood within the subband but also across the subband, the proposed method exploits the local structure of wavelet coefficients as well as high correlation of adjacent wavelet scales. The effectiveness of the proposed approach is tested and demonstrated with both simulated and measured power-line disturbance data, and the results show that the proposed scheme significantly outperforms existing methods used to denoise PQ data.