电化学噪声直流漂移的分段多项式拟合消除

在电化学噪声用于工业现场腐蚀监测过程中，如何从大量原始信号中有效去除直流漂移并恢复有用信号，具有重要意义。本文提出了一种多段m次多项式拟合法，以消除噪声数据中直流漂移成分，并采用小波分析法对消除结果的正确性进行了讨论。通过对0.5 mol/L NaCl体系中产生的噪声数据进行处理表明，窗口大小和多项式的最高方次共同影响低频数据的消除结果以及能量分布谱（EDP）的波动特征，窗口大小由腐蚀特征决定，而多项式最高方次不宜超过3。与多项式拟合法相比，分段多项式拟合法具有较高的灵活性。

TREND REMOVAL IN THE ANALYSIS OF ELECTROCHEMICAL NOISE BY POLYNOMIAL FITTING WITH WINDOW TECHNIQUE

Removing DC drift from the original electrochemical noise (EN) signal was required for recovering the EN data before calculating standard deviations and power spectral densities. In this article, a real-time method, which brings up polynomial fitting using window technique, has been applied to remove the trend of the experimental data for Q235 carbon steels in 0.5 mol/L NaCl solution, and the validity of trend removal was discussed with the energy distribution plots (EDPs). The results showed that the order and window size can corporately influence the removing results and the characteristic of the EDPs. In order to attenuate the low-frequency components without damage the useful information, the lower polynomial order (no bigger than 3)and appropriate size (between 1024 and 4096), which was determined by characteristics of EN fluctuations, should be selected.