Role of Artificial Intelligence (AI) and Machine Learning (ML) in the Corrosion Monitoring Processes - Review paper

Aug 4, 2026

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Corrosion monitoring systems are essential for the upkeep of engineering structures across diverse industries, especially in high-risk applications such as hazardous-chemical storage tanks and load-bearing construction components. Failures can lead to catastrophic outcomes, so modern approaches apply artificial intelligence and machine learning to efficiently detect corrosion damage and support minute-by-minute monitoring. This review analyzes AI/ML corrosion-monitoring applications across industries, outlines domain-specific solutions, and aims to identify suitable monitoring techniques for different corrosion-related disorders while reducing maintenance-related technical costs.

LanguageEnglish

CategoryResearch & Report

FormatPDF

Pages8

Reading Time20 min

AccessFree to download

Introduction

AI/ML in structural maintenance and corrosion monitoring

Review Analysis

Maritime pipelines and corrosion evaluation

Real-time testing and failure prevention insights

Instrumentation and characterization methods

Rajasekaran Saminathan 1 *, Abdulla Yahya Ali Nashali2, Abdulrahman Ahmed Ali Haqawi3, Shanmugasundaram Marappan4, Shanmuga Priya Natesan5, Farah Shakeel6 1-3Department of Mechanical Engineering, College of Engineering and Computer Sciences, Jazan University, Saudi Arabia, 4Department of AI & ML, BMSIT & M, Bangalore, India, 5Deptartment of Mechanical engineering, Siddaganga Institute of Technology, Tumkur. Karnataka, India, 6Lecturer, Department of English, AlArdah University College, Jazan University, Saudi Arabia Review paper ISSN 0351-9465, E-ISSN 2466-2585 [https://doi.org/10.62638/ZasMat1](https://doi.org/10.62638/ZasMat1) 192 Zastita Materijala 65 (3) 473-480 (2024) Role of artificial intelligence (AI) and machine learning (ML) in the corrosion monitoring processes ABSTRACT When it comes to the upkeep of engineering structures in a variety of industries, corrosion monitoring systems are an extremely important components. In particular, applications such as storage tanks for hazardous chemicals and weight-bearing structures of large engineering constructions are at the forefront of providing attention to relevance. This is due to the fact that failures experienced by these applications can potentially result in catastrophic consequences. Asa result, contemporary methods make use of the application of concepts connected with machine learning and artificial intelligence in order to efficiently monitor and identify corrosion related damges. As a consequence of this, the monitoring system is able to provide the control of the industrial structures with minute-by-minute updates. Therefore, the catastrophe is prevented to a significant degree, and there is a significant possibility of lowering the costs associated with technical procedures that require maintenance. Within the scope of this paper, a comprehensive analysis is conducted on the applications of artificial intelligence and machine learning techniques that are utilized in corrosion monitoring systems across a wide range of industries. Through this assessment, the solutions and efficient corrosion monitoring methods that are specific to the domains made available. Consequently, the purpose of this work is to determine the appropriate technique of monitoring systems for each and every corrosion-related disorder. Keywords: Artificial Intelligence, machine learning, corrosion monitoring system, oil and gas industries 1. INTRODUCTION It is possible to make effective use of artificial intelligence and machine learning in the maintenance of engineering structures such as bridges, heavy buildings, and water pipelines, among other types of structures [1-3] . The construction industry has begun to implement artificial intelligence and machine learning in order to optimize and automate the production processes, which are essential for the completion of a project in a shorter amount of time. Consequently, for the purpose of optimizing the production phases and the construction activities Corresponding author: Rajasekaran Saminathan E-mail: [rsaminathan@jazanu.edu.sa](rsaminathan@jazanu.edu.sa) [Paper received: 31](Paper received: 31) . 01. 2024. Paper corrected: 29. 02. 2024. Paper accepted: 12. 03. 2024. Paper is available on [the website: www.idk.org.rs/journal](the website: www.idk.org.rs/journal) that came before them, artificial intelligence analysis is used to the numerous processes that are involved in construction projects [4,5] . Some examples of corrosion monitoring systems include the monitoring of pipeline corrosion, the monitoring of heavy engineering structures utilized in the oil and gas industries, and the monitoring of the health of chemical storage tanks. A combination of artificial intelligence and machine learning is utilized by these systems in order to determine the important components that correspond to the failure modes of structures [6,7] . When it comes to structural applications, aluminum alloys are gradually replac

FAQs

Why are corrosion monitoring systems important in engineering industries?

They support safe upkeep of engineering structures, particularly for high-risk applications where corrosion-related failures can cause severe consequences.

How do AI and ML improve corrosion monitoring?

They help monitor and identify corrosion damage efficiently and enable frequent updates, supporting analysis of failure modes and corrosion behavior.

What does the review paper focus on?

It provides a comprehensive analysis of AI/ML techniques used in corrosion monitoring systems, summarizing solutions across industries and matching techniques to corrosion disorders.

Aug 4, 2026

Upload by Levi