BOPVis: Bridge Monitoring Data Visualization for Operational Performance Mining

Abstract

Bridges are fundamental facilities in the transportation system, and their operational performance is crucial for economic and social development. Many large bridges are now equipped with structural health monitoring (SHM) systems that collect various types of real-time data. However, our user study found that despite the accumulation of massive amounts of monitoring data, current analysis methods cannot efficiently process large-scale, high-dimensional data. To address this, we have developed BOPVis, a visualization system for bridge monitoring data. BOPVis allows users to intuitively locate sensors and extract corresponding data from a 3D digital model of a bridge. It also provides convenient and flexible interactions for examining trends over time and correlations across hundreds of monitoring channels. A real-world long-span suspension bridge in China is used as a case study to demonstrate the advantages of the BOPVis system for operational performance mining. Through BOPVis, the global temperature deformation behaviors of the bridge are explored and found to align with the physical mechanism documented in the SHM literature. The BOPVis system, with its interactive visualization analysis capabilities, offers a new method for analyzing bridge monitoring data.

Keywords

• bridge monitoring
• data visualization
• operational performance
• data mining