On the detection of corrosion pit interactions using two-dimensional spectral analysis

Abstract

A particular thanks to Professor Maxence Bigerelle (UTC, Compiègne, France) and to research and development engineer Dr. Benjamin Fournier (CEA, Saclay, France) for their interesting discussions and useful advices about the scientific problem of pitting corrosion.A statistical methodology for detecting pits interactions based on a two-dimensional spectral analysis is presented. This method can be used as a tool for the exploratory analysis of spatial point patterns and can be advanced as an alternative of classical methods based on distance. One of the major advantages of the spectral analysis approach over the use of classical methods is its ability to reveal more details about the spatial structure like the scale for which pits corrosion can be considered as independent. Furthermore, directional components of pattern can be investigated. The method is validated in a first time using numerical simulations on random, regular and aggregated structures. The density of pits, used in the numerical simulations, corresponds to that assessed from a corroded aluminium sheet. In a second time, this method is applied to verify the independence of the corrosion pits observed on the aforementioned aluminium sheet before applying the Gumbel theory to determine the maximum pit depth. Indeed, the property of independence is a prerequisite of the Gumbel theory which is one of the most frequently used in the field of safety and reliability.International audienceA statistical methodology for detecting pits interactions based on a two-dimensional spectral analysis is presented. This method can be used as a tool for the exploratory analysis of spatial point patterns and can be advanced as an alternative of classical methods based on distance. One of the major advantages of the spectral analysis approach over the use of classical methods is its ability to reveal more details about the spatial structure like the scale for which pits corrosion can be considered as independent. Furthermore, directional components of pattern can be investigated. The method is validated in a first time using numerical simulations on random, regular and aggregated structures. The density of pits, used in the numerical simulations, corresponds to that assessed from a corroded aluminium sheet. In a second time, this method is applied to verify the independence of the corrosion pits observed on the aforementioned aluminium sheet before applying the Gumbel theory to determine the maximum pit depth. Indeed, the property of independence is a prerequisite of the Gumbel theory which is one of the most frequently used in the field of safety and reliability

A generic statistical methodology to predict the maximum pit depth of a localized corrosion process

“…This attraction domain of the pit depth distribution is confirmed when looking at Fig. 11a presenting the evolution of the UH estimator of Beirlant et al [14,49], n UH , as a function of the number of maxima, k, which corresponds to the selected number of greatest pit depths. The confidence interval presented on this figure has been calculated by means of a bootstrap method.…”

“…In literature, the most common method for safety or reliability was found in the application of the statistical extreme value analysis using the Gumbel methodology to predict the maximum pit depth that will be found in a large scale installation by using a small number of samples with a small area [1][2][3][4][5][6][11][12][13][14]17,18]. This methodology is based on the estimation of the two parameters of the Gumbel distribution.…”

“…Pitting corrosion is an extremely dangerous form of localized corrosion since a perforation resulting from a single pit can cause complete in-service failure of installations like water pipes, heat exchanger tubes or oil tank used for example in chemical plants or nuclear power stations [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16]. The pits depth distribution is an important characteristic of the extent of such damage; the deeper the pits, the more dramatic the damage.…”

Method of studying corrosion processes of metal electrodes by surface voltage fluctuations

“…At constant current, electrochemical reaction is monitored using the potential of corroding surface or current that flows through it [3]. At alternating current, the equivalent circuit of layered electrolyte structure near the corroding surface is built for electrochemical reaction study [4] or spectral characteristics of measured signals are analyzed [5].…”

Detection of Surface Roughness Evolution of Carbon Steel Subjected to Outdoor Exposure and Constant Humidity Corrosion Tests

“…Wang 6) detected corrosion pits via optical images using gradient-based Hough transform, which detects pits with a variety of radii and depths. Jarrah 7) observed corrosion pit interactions by two-dimensional spectral analysis and established it as a powerful technique to distinguish spatial data.…”