Full-scale performance evaluation of bridges using dynamic and static instrumentation

Abstract

Structural Health Monitoring (SHM) is a popular research topic comprising a range of activities from sensor development to data mining. The essence of SHM is learning about the ‘state’ of a bridge by measurements of response parameters, along with loads such as temperature and wind. The state of the bridge is defined by a range of structural and response parameters. The aim of SHM is to check the state of the bridge against acceptance criteria (e.g. over-loaded or damaged) and to indicate changes to the state, signaling changes to the structure or the loading. To do this requires a combination of condition assessment, a detailed assessment or snap-shot of the structure including analytical modeling, inspection and dynamic testing, followed by long term but less detailed monitoring of performance using permanent instrumentation. Using few sensors and a well-developed understanding of the structure from the condition assessment, the long term monitoring serves to check that performance is within bounds, and provides indication of altered state, which can signal more detailed (condition) assessment to fully diagnose the likely fault. This paper describes condition assessment and long term monitoring of example bridges and how new technology is applied to improve the capability to detect and diagnose anomalous structural performance in real time in order to provide timely alerts for bridge operators to take action.