Fractal characteristic analysis of electrochemical noise with wavelet transform
Source abstract
Abstract
In the study, the fractal parameters were introduced to describe the irregular characteristic of electrochemical noise, which were calculated with wavelet transform to overcome some defects of other methods. Compared with other fractal parameters, wavelet standard deviation (STD) exponent (Hws) had smaller deviation and could describe the fractal characteristics of electrochemical noises in a wide range, therefore Hws was chosen to evaluate general and local irregularity of potential signals generated from 7075-T76 aluminum alloy in 3.5% NaCl solution without and with different inhibitors respectively. The results showed that the smaller general Hws value, the more frequently potential fluctuated on the electrode surface, and the less effect of inhibitor in the solution. The difference between general Hws and 1 reflected the condition of surface passivity. Local Hws could effectively extract the local feature of electrochemical noise and quantitatively describe the change of its fractal characteristic with time, which was a promising index to analyze electrochemical noise in practice.
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Research context
OpenAlex topics: Complex Systems and Time Series Analysis · Neural Networks and Applications · Image and Signal Denoising Methods
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