The characteristics of transients or peaks in electrochemical noise (EN) data were assessed by inspection from two systems. One was UNS G10100 in Ca(OH)2/NaCl solution and the other was a magnesium alloy (ZA1040) in Mg(OH)2/NaCl solution. Each system exhibited a variety of both sharp and broad peaks. Directly measured quantities include the location in the time record, the current and potential amplitudes, the area under each peak (as coulombs) and the direction (maximum or minimum). The frequencies of transients are readily assessed given their location in the time record. Inferred quantities include the polarization resistance of the responding electrode and the nature of the transient (anodic or cathodic). Progress for computer-based techniques for reliably finding transients within a set of EN data is described. One promising approach is that locations in the time record where the current derivative crosses zero correlates with the apex of simple rounded peaks. However, this is not true of broad or noisy peaks. A promising approach is to apply data smoothing to round broad or noisy peaks and permit the derivative to identify the apex. This pre-processing of EN data may enable artificial neural networks to accurately locate peaks. This work also suggested that the sampling frequency influences the number and type of transients detected and thus should be tuned to each particular system. It also suggested that consideration be given to the experimental arrangement to ensure that the current and potential are correlated during transients.
Electrochemical noise (EN) data are measurements of current between two nominally similar electrodes and the potential between this couple and a reference electrode as a function of time. The promise of EN data is that it can yield information regarding both localized corrosion processes as well as provide a measure of the uniform corrosion rate. Statistical and frequency-domain techniques have been applied with varying degrees of satisfaction to achieve both of these ends1. In the analysis of EN data in the time domain analysis, information from each transient is extracted. These transients are understood to be usually due to localized corrosion processes. Of interest are their intensity and frequency. It is also possible to obtain the self linear polarization resistance (SLPR) of the responding electrode given a measure of the amplitude of potential and amplitude of current2-5.
Analysis of individual transients or peaks in the time domain is applied in spectroscopic measurements such as from a gas chromatograph and mass spectrometer. A method for identifying and characterizing transients in EN data was introduced in a previous work4. The apex of each peak was identified as that where the derivative of both current and potential each crossed zero. However, further assessment revealed that this was not completely satisfactory. Inspection of raw EN data indicated that not all peaks were identified and some were that should not have been selected. This work re-assessed the approach of using the current derivative to find peaks based on inspection of EN data from two systems. Both systems were known to produce transients. In the first (a magnesium alloy in saline/Mg(OH)2), a small number of meta-stable pits of the order of 1 mm diameter in size were known to occur based on SRET measurements6. In the second (G10100 in Ca(OH)2/saline), transients had been previously observed7.
