Development of Delamination Detection System for Concrete Decks by Using Convolutional Neural Network

Proceedings

Guillamón, Juan José Rubio¹  Kashiwa, Takahiro²  Nagai, Kohei³  Ibayashi, Kou⁴  Prendinger, Helmut⁵  Tatsuta, Hitoshi⁶ 

[1] Barcelona School of Informatics, Universitat Politècnica de Catalunya, 08034 Barcelona, Spain;Faculty of Engineering, The University of Tokyo, Tokyo 153-8505, Japan;Institute of Industrial Science, The University of Tokyo, Tokyo 153-8505, Japan;Nagaoka National College of Technology, Niigata 940-8532, Japan;National Institute of Informatics, Tokyo 101-8430, Japan;Nippon Engineering Consultants CO., LTD., Tokyo 170-0003, Japan

关键词: damage detection;    delamination;    regular inspection;    machine learning;    fully convolutional network;   

DOI  :  10.3390/ICEM18-05281

学科分类：社会科学、人文和艺术（综合）

来源: mdpi

【 摘 要 】

Bridges in Japan, especially those managed by municipalities, deteriorate over time. Due to lack of civil engineers in municipalities, appropriate and automated assistance for degradation judgement is thought to be important for the concerned authorities. Automated judgement systems for some types of damage (e.g., cracks) started to be developed by geometrical approaches. Yet, there is no comprehensive method to detect more complicated types of damage, such as delamination, for regular inspection. This research aims to develop a delamination-detection system which identifies the location of the damage. Images with delaminated parts were provided by Niigata Prefecture (in Japan), and annotation of the location of delamination and/or rebar exposure was conducted. Fully Convolutional Network (FCN), one of the deep learning networks for pixel-to-pixel segmentation, was used to detect the areas of the delamination and rebar exposure. The result of the training aided by FCN showed a good agreement with the result with the naked eye. The soundness, judged based on the FCN result according to the inspection code of Niigata Prefecture, was close to the soundness judgement at the site. These outcomes support the reliability of the system to detect delamination and rebar exposure in manual inspection. This technology is expected to be used in bridges’ inspection at municipalities, which have a lack of inspection engineers.

【 授权许可】

CC BY