Abstract：The power quality signals acquired from the locale contain gaussian white noise and impulse noise,which bring difficulty to the detection and analysis of power quality signals, so the power quality signals should be adopted to perform denoising pretreatment. Aiming at the limitation of the traditional denoising methods, the denoising method based on tunable Q-factor wavelet transform and basis pursuit is given in this paper. Firstly, the wavelet basis functions with different Q-factor are adopted to perform the signal sparse decomposition for the noisy signals; secondly, the BP denoising algorithm is used to optimize the obtained wavelet coefficients; lastly, the optimized wavelet coefficients are reconstructed, then the main characteristics of power quality signal, gaussian white noise and impulse noise are separated, which can achieve the purpose of denoising. The simulation results show that this method can effectively remove the white gaussian noise and impulse noise from the power quality signal, and the denoising effect and reliability is superior to the widely used wavelet denoising and ensemble empirical mode decomposition denoising.
2016, Vol. 17 
