Fractional Order Signal Processing of Electrochemical Noises

Author:

Yangquan Chen 1,Rongtao Sun 2,Anhong Zhou 3,Zaveri Nikita4

Affiliation:

1. Center for Self-Organizing and Intelligent Systems, Department of Electrical and Computer Engineering, Utah State University, Logan, UT 84322-4120 USA ,

2. Center for Self-Organizing and Intelligent Systems, Department of Electrical and Computer Engineering, Utah State University, Logan, UT 84322-4120 USA

3. Department of Biological and Irrigation Engineering, Utah State University, 4105 Old Main Hill, Logan, UT 84322-4105 USA,

4. Department of Biological and Irrigation Engineering, Utah State University, 4105 Old Main Hill, Logan, UT 84322-4105 USA

Abstract

The corrosion processes of stainless steel under different solutions were examined using electrochemical noise (ECN). Using rescaled range analysis, we demonstrated that ECN signals produced by corrosion processes have non-stationary and self-similar properties. The comparison and analysis of ECN signals in both the time and frequency domains showed that conventional methods failed to sufficiently distinguish between the ECN signals obtained under different solutions. Therefore, we introduced the use of fractional Fourier transforms, a powerful tool for the time-frequency analysis of self-similar signals, to process ECN signals that can better describe the corrosion behaviours of the electrode in different solutions.

Publisher

SAGE Publications

Subject

Mechanical Engineering,Mechanics of Materials,Aerospace Engineering,Automotive Engineering,General Materials Science

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