journal article·2003-09

Electrochemical noise analysis for estimation of corrosion rate of carbon steel in bicarbonate solution

Takumi Haruna, Yasuyuki Morikawa, Shinji Fujimoto, Toshio Shibata

Corrosion Science· Volume 45· Issue 9
Publisher page

Abstract

Abstract We have investigated the electrochemical noise behavior of carbon steel in fully deaerated aqueous bicarbonate solutions, and discussed the optimum conditions of the noise analysis for estimating corrosion rate of the steel. Noise of the potential difference and of the short-circuit current between two identical steel coupons were successfully measured. The time-series noise patterns were transformed into frequency domain by fast Fourier transformation, and then their power spectrum densities (PSDs) at a frequency were determined to be compared with the corrosion rate. The PSDs of the potential and of the current varied with changing environmental factors of bicarbonate concentration, pH, and immersion time. The factors also controlled the corrosion rate of the steel. The PSDs were associated with the corrosion rate, and then it was found that the PSDs of the potential and of the current showed linear correlation with the corrosion rate in log–log scale. There was also linear relationship between the corrosion rate and a spectral noise resistance obtained from the PSDs of the potential and the current. The linearities of the three correlations were better at a lower analyzed frequency. Furthermore, the PSDs of the current and the noise resistance indicated more linear correlation with the corrosion rate than that of the potential. As the simplicity of the measurement system is additionally considered, it is concluded that the PSD of the current noise at an analyzed frequency of 3 mHz is the optimum conditions for estimating the corrosion rate from 10−2 to 100 A m−2 in this study.
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Research context

OpenAlex topics: Corrosion Behavior and Inhibition · Hydrogen embrittlement and corrosion behaviors in metals · Non-Destructive Testing Techniques

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

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