基于小波变换的循环伏安弱信号特征信息提取

Method for Extracting Weak Cyclic Voltammetric SignalCharacteristic Information Based on Wavelet Transformation

本研究采用连续小波变换(continuouswavelettransform,CWT)技术处理循环伏安弱信号,通过研究苯酚、对苯二酚和对硝基苯酚的共存体系循环伏安弱信号,表明CWT可以成功地识别出极弱信号中的指纹特征信息,并且经处理得到的对应的小波系数峰比原始信号更窄,更高,由此可以成功地确定弱峰的数目和位置。由循环伏安信号所得的结果,有力地证实CWT是循环伏安弱信号识别的有力工具,对于理解弱响应体系电化学机理具有重要作用。

In this paper, we paid our attention to process the weak cyclic voltammetric signals of a complex system adopting the skill of continuous wavelet transform ( CWT). By studying the weak cyclic voltammetric signals of the concomitant system of three hydroxybenzenes, namely phenol, hydroquinone and nitrophenol, it was shown that this skill could successfully distinguish the fingerprint-characteristic information from the very weak signal, and it was found also that the processed corresponding wavelet coefficient peaks were narrower and higher than the original signals, which in turn, helped to successfully identify both the number and location of the weak peaks. The results obtained from the weak cyclic voltammetric signals strongly confirmed that proposed CWT was a powerful tool of identifying processing and could greatly help to understand the weakly-responded system's electrochemical mechanism.