DEVELOPMENT OF JUDGEMENT SUPPORT SYSTEM OF SURFACE PREPARATION FOR STEEL STRUCTURES USING DEEP LEARNING

OHYA Makoto, SUWA Taiki, GOBARA Tatsuya, TAKEBE Masamichi, HIROSE Nozomu

doi:10.11532/jsceiii.2.j2_771

<p>The quality and durability of repair coatings for steel bridges are significantly affected by the surface preparation prior to repair coating. Surface preparation by blasting stipulated by ISO Sa2 1/2 or higher is required as surface treatment before repair coating. The judgement of the preparation grade is enforced by visual inspection. However, it is difficult for inexperienced field supervisors to not only accurately judge of the preparation grade, but also make quantitative decisions. In this paper, we try to develop a system that supports the judgment of the preparation grade on steel surface before repair coating using deep learning. This study targets rust grade D of weathering steels. As training data for deep learning, we use blasted images pre-graded by experts. An unknown image is applied to the established system, and it is evaluated whether it can be appropriately classified into four classes from ISO Sa1 to Sa3. However, this study did not provide enough teacher images to ensure accuracy. Therefore, two approaches were tried to solve this problem. The system was applied, firstly, an extension technique of number images and, secondly, the use of a trained model. It was confirmed that the developed system using deep learning enables highly accurate classification of the preparation grade of rust removal after blasting. </p>

DEVELOPMENT OF JUDGEMENT SUPPORT SYSTEM OF SURFACE PREPARATION FOR STEEL STRUCTURES USING DEEP LEARNING

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