EFFECTS OF CNN MODELS AND DIFFIRENT DIGITAL IMAGE RESOLUTION ON ACCURACY OF RUST CONDITION RATING OF WEATHERING STEEL

Abstract

The inspection and diagnosis of weathering steel bridges is based on the deterioration of anti-corrosion function, which is evaluated with the corrosion condition rating by observation. However, in order to perform an accurate evaluation by therating, inspectors need to have necessary to have adequate experience. Due to the recent shortage of human resources and inspection costs, it is needed to establish a simple and accurate evaluation method. In this study, the identification of rust condition has been investigated by using digital images of surface rust condition in weathering steel bridges and existing CNN models. Inaddition, the effect of digital image resolution on the identification accuracy has been considered. As a result, the accuracy isrelatively high in the case of VGG19 and SEnet. The larger input image size gives the better accuracy. Furthermore, the accuracy tends to decrease when the resolution of the images used for training and validation is different.