An Integrated Coating Inspection System for Marine and Offshore Corrosion Management

The application of protective coatings is the primary method for protecting marine and offshore structures from coating breakdown and corrosion (CBC). The CBC assessment is a major aspect of coating failure management. Evaluation methods can result in unnecessary maintenance costs and a higher risk of failure. In order to improve efficiency and productivity, the micro-aerial vehicle (MAV) auxiliary automated CBC Evaluation System (A-CAS) is proposed for effective coating failure inspection. Compared to existing manual inspection solutions by surveyors, this method is more suitable for inspecting large areas by means of capturing and analyzing pictures/videos of the target areas. In this paper, a MAV facilitated CBC assessment system implementing deep learning for object recognition has been developed to provide effective CBC assessment for marine and offshore industries. By using active thermography, it is able to identify corrosion behind coatings. This will greatly improve the work efficiency and reliability of coating inspection for surveyors.