Application of Artificial Intelligence in Marine Corrosion Prediction and Detection

Author:

Imran Md Mahadi Hasan1,Jamaludin Shahrizan1ORCID,Ayob Ahmad Faisal Mohamad1ORCID,Ali Ahmad Ali Imran Mohd1,Ahmad Sayyid Zainal Abidin Syed1ORCID,Akhbar Mohd Faizal Ali1,Suhrab Mohammed Ismail Russtam2ORCID,Zainal Nasharuddin3ORCID,Norzeli Syamimi Mohd4,Mohamed Saiful Bahri4ORCID

Affiliation:

1. Faculty of Ocean Engineering Technology and Informatics, Universiti Malaysia Terengganu, Kuala Terengganu 21030, Terengganu, Malaysia

2. Faculty of Maritime Studies, Universiti Malaysia Terengganu, Kuala Terengganu 21030, Terengganu, Malaysia

3. Department of Electrical, Electronic and Systems Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, Bangi 43600, Selangor, Malaysia

4. Faculty of Innovative Design and Technology, Universiti Sultan Zainal Abidin, Kuala Terengganu 21030, Terengganu, Malaysia

Abstract

One of the biggest problems the maritime industry is currently experiencing is corrosion, resulting in short and long-term damages. Early prediction and proper corrosion monitoring can reduce economic losses. Traditional approaches used in corrosion prediction and detection are time-consuming and challenging to execute in inaccessible areas. Due to these reasons, artificial intelligence-based algorithms have become the most popular tools for researchers. This study discusses state-of-the-art artificial intelligence (AI) methods for marine-related corrosion prediction and detection: (1) predictive maintenance approaches and (2) computer vision and image processing approaches. Furthermore, a brief description of AI is described. The outcomes of this review will bring forward new knowledge about AI and the development of prediction models which can avoid unexpected failures during corrosion detection and maintenance. Moreover, it will expand the understanding of computer vision and image processing approaches for accurately detecting corrosion in images and videos.

Funder

Ministry of Higher Education Malaysia (MOHE) through Fundamental Research Grant Scheme

Universiti Malaysia Terengganu (UMT) through Talent and Publication Enhancement Research Grant

Publisher

MDPI AG

Subject

Ocean Engineering,Water Science and Technology,Civil and Structural Engineering

Reference225 articles.

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