Structural health monitoring of the Tamar suspension bridge

Abstract

This paper presents experiences and lessons from the structural health monitoring practice on the Tamar Bridge in Plymouth, UK, a 335-m span suspension bridge opened in 1961. After 40 years of operations, the bridge was strengthened and widened in 2001 to meet a European Union Directive to carry heavy goods vehicles up to 40 tonnes by a process in which additional stay cables and cantilever decks were added and the composite deck was replaced with a lightweight orthotropic steel deck. At that time, a structural monitoring system comprising wind, temperature, cable tension and deck level sensors was installed to monitor the bridge behaviour during and after the upgrading. In 2006 and 2009, respectively, a dynamic response monitoring system with real-time modal parameter identification and a robotic total station were added to provide a more complete picture of the bridge behaviour, and in 2006 a one-day ambient vibration survey of the bridge was carried out to characterize low-frequency vibration modes of the suspended structure. Practical aspects of the instrumentation, data processing and data management are discussed, and some key response observations are presented. The bridge is a surprisingly complex structure with a number of inter-linked load-response mechanisms evident, all of which have to be characterized as part of a long-term structural health monitoring exercise. Structural temperature leading to thermal expansion of the deck, main cables and additional stays is a major factor on global deformation, whereas vehicle loading and wind are usually secondary factors. Dynamic response levels and modal parameters show apparently complex relationships among themselves and with the quasi-static load and response. As well as the challenges of fusing and managing data from three distinct but parallel monitoring systems, there is a significant challenge in interpreting the load and response data firstly to diagnose the normal service behaviour and secondly to identify performance anomalies. Copyright © 2012 John Wiley & Sons, Ltd. Copyright © 2012 John Wiley & Sons, Ltd.