Improved visualization of infrastructure monitoring data using building information modeling

Abstract

With growing complex infrastructure, autonomous condition assessment of large-scale structures has garnered significant attention over the past few decades. Data-driven structural health monitoring (SHM) techniques offer valuable information of existing health of the structures, maintain the safety and their uninterrupted use under varied operational conditions by undertaking timely risk and hazard mitigation. Traditional approaches, however, are not enough to monitor a large amount of SHM data and conduct systematic decision making for future maintenance. In this article, building information modeling (BIM) is utilised as a promising computing environment and integrated digital representation platform of SHM that can organize and visualise a considerable amount of sensor data and subsequent structural health information over a prolonged period. A BIM-enabled platform is utilised to develop the proposed visualisation tool for a long-span bridge and enable automated sensor data inventory into the BIM environment. Such automated tool facilitates systematic maintenance and risk management, while avoiding manual errors resulting from visual inspection of the structures. The proposed method can be considered as a user-friendly and economic framework for condition assessment and disaster mitigation of structures from long-term monitored data.

Keywords:

• Structural health monitoring (SHM)
• building information modeling
• system identification
• long-term monitoring
• visualisation tool
• Revit
• big data

Acknowledgements

This research was funded by NSERC Discovery and Engage grants of the second author. In-kind contributions and assistance from WSP Canada Inc. during the bridge instrumentation were greatly acknowledged.