小波熵自适应阈值的电能质量信号去噪新方法

针对电能质量信号去噪问题,提出改进的小波熵自适应阈值去噪法。利用小波变换分解电能质量信号,计算小波分解后信号子带区间的小波熵,将小波熵和自适应阈值相结合确定高频系数阈值门限,采用改进折中指数阈值函数对电能质量信号去噪处理,最后重构降噪后的电能质量信号。通过对四种典型带噪电能质量信号(电压突降信号、暂态振荡信号、电压中断信号、谐波信号)去噪处理,并与无偏风险阈值、极大极小阈值的去噪性能比较,对比可知在输入信噪比为20dB时,对于不同的电能质量信号,改进的小波熵自适应阈值去噪法的输出信噪比是最大的。

Denosiong method for electrocardiogram signal based on wavelet entropy and adaptive threshold

For the problem of power quality signal denoising,an adaptive threshold extraction method based on wavelet entropy is presented in this paper. The signal was disposed of wavelet decompositon, the power quality signal at decomposed levels wavelet entropy can be calculated. The wavelet entropy and adaptive threshold are combined to decided the threshold of high frequency coefficients. Compromised improved index threshold function is used to denosied power quality signals, then power quality signals are reconstructed. Compared with denoising the four typical power quality signals(voltage sag signal,voltage transient oscillatory signal, voltage interruption signal and harmonic signal)with the methods of rigrsure threshold,max-min threshold and the proposed method,the simulation results show that the input signal-to-noise ratio is 20dB, for different power quality signal, output signal-to-noise ratio of improved wavelet entropy adaptive threshold is the biggest.