Digital representation of as-damaged reinforced concrete bridges

Abstract

Inspection of bridges has been a standard assessment procedure for decades. Its purpose is to identify and record all defects of the bridge structure. Normally used inspection techniques are rather simple, mainly relying on visual assessment. This dissertation proposes an improvement of concrete bridge inspection in terms of visual data acquisition, damage identification and digital representation of the bridge with identified damages. Instead of depending strictly on the human eye, photogrammetrically obtained 3D point clouds are used to identify and extract concrete damage features. As the most comprehensive substitute for the old-fashioned inspection report, Bridge Information Model (BrIM) is used as an inventory and inspection data repository. An Industry Foundation Classes (IFC) semantic enrichment framework is proposed to inject the extracted and reconstructed damage features into the as-is IFC model. After the general data model for damage description and its IFC representation are established, the method for generating the as-is IFC model of the bridge is proposed. Damage is identified as a deviation of the as-is geometry, represented by the 3D point cloud, from the as-built geometry, represented by BrIM. Geometric and semantic enrichment of the IFC model is achieved by injecting the reconstructed 3D meshes representing damaged regions and corresponding BMS catalogbased damage information. The proposed method uses Constructive Solid Geometry (CSG) Boolean operations to geometrically enrich the IFC geometry elements, which align with corresponding damage regions from the as-is point cloud. Damage information (e.g., type, extent, and severity) is structured so that it complies to the BMS data structure. Finally, the proposed data model, damage identification, feature extraction, and semantic enrichment method are validated in the presented case study.