Bridge Inspection Using Bridge Information Modeling (BrIM) and Unmanned Aerial System (UAS)

Abstract

Bridge inspection is a critical task that is needed to monitor bridge quality and serviceability. Previous studies indicate that road network and bridges in the U.S. are not of high quality and poorly maintained for decades, and the current manual inspection routine is expensive, time-consuming, hazardous, and subjective. Moreover, current Bridge Management Systems (BMS) may not coordinate management of all phases of the bridge life cycle. Also, the dispersed inspection data drastically reduces the effectiveness of the system. Therefore, there is a need to identify cost-efficient and productive ways to inspect and manage our bridges. The objective of this study is to develop a novel framework for bridge inspections and management. The framework implements Bridge Information Modeling (BrIM) and Unmanned Aerial Systems (UASs) technologies in an integrated manner to solve the issues associated with current manual bridge inspection and management practice. The proposed framework was implemented using data collected from an existing bridge located in Eugene, Oregon. Different types of defects were identified automatically using computer vision algorithms from the digital images captured by the UAS. These defects were assigned to individual BrIM elements. BrIM was used as the central database to store the 3D bridge model and inspection data. The framework also enables bridge inspectors and decision makers to access the most up-to-date inspection data simultaneously by taking advantage of cloud computing technology. The proposed framework: (1) provides a systematic approach for accurately documenting the structural condition assessment data, (2) reduces the number of site visits and eliminates potential errors resulting from data transcription, and (3) enables a more efficient, cost-effective and safer bridge inspection process.