earticle

영어

Quality control is difficult to secure objectivity because the quality management of reinforced concrete construction is made by the subjective judgment by experts through a checklist. This study aims to establish an automation process for quality management of reinforced concrete frameworks through a Deep Learning algorithm based on object recognition. Through this, it is possible to save time more objectively than before, and the purpose is to provide intuitive judgment through visualization. This study proposed a quality control process through the learning and verification process with the image data set obtained from AI Hub, and mAP was derived with an accuracy of 0.687. The drone image data of the actual site was determined using the derived algorithm. 3D modeling is performed through the determined drone image to ensure the safety of the inspector and intuitive judgment. The proposed process cannot be confirmed the determined line when matched with a 3D model using PIX4D, but it is judged that it will be applicable to additional processes through the replacement of modeling programs and improvement of Deep-Learning algorithms.