A Bridge Damage Visualization Technique Based on Image Processing Technology and the IFC Standard

Yuan Tian, Xuefan Zhang, Haonan Chen, Yujie Wang and Hongyang Wu ()
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Yuan Tian: Transportation Technology Development Promotion Center, China Academy of Transportation Sciences, Beijing 100029, China
Xuefan Zhang: College of Transportation Engineering, Dalian Maritime University, Dalian 116026, China
Haonan Chen: College of Transportation Engineering, Dalian Maritime University, Dalian 116026, China
Yujie Wang: School of Civil Engineering, Beijing Jiaotong University, Beijing 100044, China
Hongyang Wu: Transportation Technology Development Promotion Center, China Academy of Transportation Sciences, Beijing 100029, China

Sustainability, 2023, vol. 15, issue 11, 1-20

Abstract: As an important part of the traffic infrastructure, the bridge has attracted much attention for its health conditions. Bridge damage detection is an important way of evaluating bridge health conditions. However, the bridge damage could not be directly expressed by traditional bridge damage detection methods. With the emergence of new technologies and engineering applications, it is possible to achieve visual expression of bridge damages, improve the digitization of bridge detection, and promote sustainable development in bridge maintenance. In this paper, a method of bridge damage visualization based on image processing technology and the IFC standard description is proposed for common bridge damages. An existing cable-stayed bridge is taken as the engineering background, and the collected damage images are processed and analyzed utilizing cutting-edge technology to obtain specific damage information such as the length and width of bridge cracks and concrete defects. Then based on the IFC standard, the bridge damage and its attribute information are visualized and stored through an established REVIT model of the bridge.

Keywords: image processing; the IFC standard; bridge damage; visualization; REVIT model (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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