龚静.电能质量信号去噪中小波选取特点的研究[J].电测与仪表,2022,59(5):129-135. Gong Jing.Research on the characteristics of wavelet selection in power quality signal de-noising[J].Electrical Measurement & Instrumentation,2022,59(5):129-135.
电能质量信号去噪中小波选取特点的研究
Research on the characteristics of wavelet selection in power quality signal de-noising
Effective de-noising in power quality signal is an important prerequisite for power quality detection; however, the wavelet features have a great impact on the de-noising effect. Aiming at this problem, an adjustable threshold function is firstly proposed. By controlling the adjustable parameters, the proposed threshold function can be changed between hard and soft threshold functions. On the basis of deeply studying the wavelet features, such as orthogonality, support length, regularity, order of vanishing moment, symmetry, etc., in order to achieve the best de-noising effect, five features of wavelet selection that should be satisfied are proposed in this paper. db 5, haar, bior 2.2 and rbio 3.1 are used to decompose voltage sag, swell, interruption, oscillation and harmonics signals into four scales. On the basis of calculating the standard deviation of noise, the operator is introduced to modify the threshold, and the new threshold function is used to de-noise the wavelet detail coefficients. After de-noising, the details of the reconstructed signal are analyzed, and the SNR and MSE are calculated. The experimental results show that db 5 wavelet has the best de-noising effect under different noise intensity, which proves the correctness and reliability of the five wavelet characteristics in power quality signal de-noising proposed in this paper.
