Evaluation of microbially influenced corrosion with electrochemical noise analysis and signal processing

Corrosion behaviors of stainless steel (SS304), with attached Acidithiobacilus ferrooxidans (ATF) bacteria and exposed to three different types of artificial saliva solutions, namely: (1) Jenkin's solution, (2) Tomasi's solution, and (3) NaCl solution, have been monitored using electrochemical noise (ECN) analysis and signal processing techniques. The ECN data has been analyzed in time and frequency domains, and the time-domain analysis was used to calculate parameters such as skewness, kurtosis and noise resistance, Rn. The corrosion mechanisms were analyzed in terms of the ranges of skewness and kurtosis. The frequency analysis showed that the conventional fast Fourier transforms (FFT) method failed to differentiate among the ECN signals obtained in different solutions with and without the attachment of bacteria. Therefore, the fractional Fourier transform (FrFT) was introduced to process ECN signals and has been demonstrated as a better tool to describe the corrosion behaviors of electrodes in different solutions.