On Population-based structural health monitoring for bridges

Abstract

The maintenance and repair of bridges (and other large scale infrastructure projects) is a major area which could benefit from Structural Health Monitoring technology. Inspections on bridges can take a long time and require many people, and are therefore conducted infrequently. This low frequency of inspection leaves the chance that damage and dangerous critical failures can occur during the long timeframes between inspections. It might even be the case that an inspection fails to identify sub-surface damage. Therefore some form of continuous monitoring is desirable, especially if such systems can reliably detect sub-surface damage. However, the application of SHM to bridges is made challenging by the cost and practicability of obtaining damage-state data for bridges. Over the lifetime of a single bridge, it is hoped that a critical failure will never occur, and only a small number of the possible damage states will occur. It is also unpractical to intentionally damage structures to obtain damage-state data. Population-based structural health monitoring seeks to overcome the obstacle of the limited data available for a single structure, by allowing data to be shared between similar structures. Bridges represent an interesting challenge for PBSHM as each bridge is unique. As such, an assessment of how similar bridges are to each other is required. To provide this assessment, one must develop an abstract representation for each bridge, and using this to perform a comparison. This paper describes the use of a general approach for assessing the similarity of structures, applied to several bridge examples which are representative of common types of bridges, to show that it can be applied in this field.