An integrated approach in the time, frequency and time-frequency domain for the identification of corrosion using electrochemical noise

Transients in electrochemical noise (EN) signals that are associated with localized corrosion typically contain frequency information that is quite localized in time. The study of these transients is therefore preferably performed using analysis procedures with high discrimination ability in both time and frequency simultaneously. The present work studies the combination of the Hilbert-Huang transform with the continuous wavelet transform, as data analysis methods that operate in time as well as in frequency, for the identification of localized corrosion. Additionally it incorporates fast Fourier transform as a technique to determine the distribution of power over frequency. Finally, it integrates the study of transient shape into the analysis of (time-) frequency properties. It is shown that the maxima in instantaneous frequency amplitudes of transients with otherwise different shapes can be similar. In the case of the presence of multiple transients in the EN signal, the cut-off frequency obtained from power spectral density plots is related to maxima in instantaneous frequency amplitudes of only a limited number of transients. (C) 2016 Elsevier Ltd. All rights reserved.