Title :
Wavelet Threshold De-noising of Power Quality Signals
Author_Institution :
Sch. of Electr. Eng., Shanghai Jiao Tong Univ., Shanghai, China
Abstract :
It is an important application of wavelet analysis in power system to de-noise power quality (PQ) signals so as to detect and locate the disturbing points. At present soft threshold and hard threshold de-noising methods are widely used. To improve the de-noising effect of PQ signals, an improved algorithm based on soft threshold and hard threshold de-noising methods is put forward. The key factor of wavelet thresholding de-noising is how to construct thresholding function and select the threshold. The method could combine the advantages of hard and soft threshold methods, and then achieve better access to estimate the threshold of wavelet coefficients by adjusting the parameters properly, making the improved threshold function between the soft and hard threshold functions. It could not only overcome the shortcomings of poor de-noising effect while using hard threshold method, but also effectively solve the difficult problem that leads to signal distortion within soft threshold method because of too smooth. The simulation results show that this method can reduce the loss of information while de-noising. The enhancement of SNR and the reduction of the RMSE indicate that the performance of our method is better than soft threshold and hard threshold de-noising methods.
Keywords :
distortion; power supply quality; signal denoising; wavelet transforms; disturbing points; hard threshold de-noising method; hard threshold method; power quality signals; power system signals; signal distortion; soft threshold de-noising method; soft threshold method; thresholding function; wavelet analysis; wavelet coefficients; wavelet threshold de-noising; Algorithm design and analysis; Fourier transforms; Noise reduction; Power quality; Semiconductor device noise; Signal analysis; Wavelet analysis; Wavelet coefficients; Wavelet packets; Wavelet transforms; Power system signals; Thresholding; Thresholding de-noising; Thresholding function; Wavelet analysis;
Conference_Titel :
Natural Computation, 2009. ICNC '09. Fifth International Conference on
Conference_Location :
Tianjin
Print_ISBN :
978-0-7695-3736-8
DOI :
10.1109/ICNC.2009.524