Classification of Corrosion Forms using Machine Learning Approach

Abstract

Currently, there are improvement approaches for corrosion detection and monitoring for various forms of corrosion, and significant outcomes have been observed. One of these modern approaches to predict the mechanism forms of corrosion is machine learning tools (ML), which has been studied and searched by experts recently because of the cost, time, and accurate efficiencies. This project is therefore aimed at investigating and evaluating a machine learning approach that can be used to detect the different corrosion forms, including visuals such as uniform and localized. Also, a review of the ranges of corrosion forms and corrosion detection methods have been used to improve and identify the ML tools.