Current Status of Image Recognition Technology in the Field of Corrosion Protection Applications

Abstract

Corrosion brings serious losses to the economy annually. Therefore, various corrosion protection and detection techniques are widely used in the daily maintenance of large metal engineering structures. The emergence of image recognition technology has brought a more convenient and faster way for nondestructive testing. Existing image recognition technology can be divided into two categories according to the algorithm: traditional image recognition technology and image recognition technology based on deep learning. These two types of technologies have been widely used in the three fields of metal, coating, and electrochemical data images. A large amount of work has been carried out to identify defects in metals and coatings, and deep learning-based methods also show potential for identifying electrochemical data images. Matching electrochemical images with the detection of defect morphology will bring a deeper understanding of image recognition techniques for metals and coatings. A database of accumulated morphology and electrochemical parameters will make it possible to predict the life of steel and coatings using image recognition techniques.