NATA阈值算法在局部放电波形提取中的应用

Application of NATA Threshold Algorithm to Extracting Waveform of Partial Discharge Pulses

目前工程应用中,局部放电小波消噪处理阈值算法广泛应用的是中值阈值算法(MAD-U),易造成有用信号的波形畸变,只适合于离线测量和局部放电脉冲幅值的检测。笔者研究了MAD-U的改进算法——基于噪声特性的自适应阈值算法(NATA)。首先研究了NATA算法的原理和构成;其次,从不同信噪比(SNR)下的阈值误差以及小波重构信号与原始信号误差两方面进行了MAD-U和NATA的比较研究。研究结果表明,MAD-U阈值算法其重构波形与原始脉冲波形的误差随信噪比SNR的增大呈指数倍增大,即高SNR的PD脉冲反而畸变严重。NATA阈值算法的误差较小且不随SNR而变化,不易造成信号波形的畸变,并且对小波分解尺度的依赖性小,适合在线检测和脉冲波形检测。

Median absolute deviation-universal （MAD-U） threshold algorithm of wavelet transform is widely used in denoising process of partial discharge（PD） measurement. However, it is only applicable for off-line measurement of PD pulse amplitude due to distortion of the output pulse. Therefore, a noise characteristic- based wavelet adaptive threshold algorithm （NATA） is proposed in this paper to improve the MAD-U threshold algorithm. Theory and structure of NATA are discussed. MAD-U and NATA algorithms are compared in the threshold error under different signal-to-noise ratio （SNR） and the error between wavelet reconstruction signal and original signal. Results show that： MAD-U algorithm exhibits an exponential increase with SNR in the error between the wavelet reconstruction waveform of PD pulse and the original waveform of PD pulse; the error of NATA is however very small and keeps stable, without distorting the waveform of PD pulse. Moreover, NATA is independent of the decomposition scale of wavelet transform, hence it is preferable for on-line measurement and waveform detection of PD pulses.