The corrosion of welded carbon steel in the presence of aqueous chloride-containing solutions at 30 °C was analyzed by use of electrochemical noise (EN) and wavelet transform analysis (WTA) in three different solution systems. It is shown that features extracted from sections of the EN signals imaged by way of wavelet scalograms could be used to identify different types of corrosion, as well as for online monitoring of corrosion. Moreover, the corroded welded steel surfaces were examined using 3D profilometry to gather information about localized defects (pits). These results demonstrated that electrochemical noise associated with wavelet transform analysis, particularly wavelet scalograms, is an effective tool for monitoring localized corrosion of welded carbon steel.

Subject
Pits, Steel surfaces, Electrochemical noise, Machinery, Sodium chloride, Wavelets, Electrochemical data, Corrosion data, Pitting, Passivation, Carbon steel, Types of corrosion, Samples
Keywords:
Welded carbon steel, Electrochemical noise, Corrosion monitoring, Wavelet Transform analysis, Unsupervised monitoring process, Machine learning
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2024
Association for Materials Protection and Performance (AMPP)
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