Arc Length method, an application of artificial intelligence in infrastructure crack monitoring
Publish place: International Conference on Civil, Architecture, Development and Reconstruction of Urban Infrastructure in Iran
Publish Year: 1399
نوع سند: مقاله کنفرانسی
زبان: English
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شناسه ملی سند علمی:
ICDU01_143
تاریخ نمایه سازی: 15 مهر 1399
Abstract:
Although manual crack inspection has been widely used for structural health monitoring over the last decades, the development of computer vision methods allows continuous monitoring and compensates the human judgment inaccuracy. In this study, an image-based method entitled, Arc Length method is introduced for extracting crack pattern characteristics, including crack width, and crack length. The method contains two major steps; in the first step, the crack zones are estimated in the whole image. Afterwards, the algorithm finds the start point, follows the crack pattern, and measures the crack features, such as crack width, crack length, and crack pattern angle. The application of this approach plays a significant role in the maintenance and crack monitoring of infrastructures, such as concrete bridges and tunnels.
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Authors
Amir Hossein Asjodi
M.Sc. Structural engineering, Sharif University
Kiarash M.Dolatshahi
Associate professor, Sharif University
Mohammad Javad Daeizadeh
M.Sc. Structural engineering, Sharif University