The harsh marine atmospheric conditions, including high temperatures, humidity, and salt spray, prevalent in the coastal areas of Hainan, pose a significant challenge to the durability of ground facilities and equipment, often resulting in corrosion and functional degradation. Hence, accurate monitoring of corrosion is paramount for maintaining coastal engineering structures. This study leveraged data from the Chinese National Center for Materials Corrosion and Protection Science to extract corrosion morphology features using image analysis techniques. Subsequently, a corrosion identification model was developed using machine learning algorithms. The model’s accuracy was validated through various evaluation metrics. The research outcomes have practical applications in the maintenance and management of coastal engineering structures by providing automatic corrosion morphology recognition. This enables maintenance personnel to promptly undertake repair measures, thereby reducing maintenance costs and enhancing structural sustainability.
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Yu et al. (2024) studied this question.
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