Bridges are expensive to manage as they require thorough inspection and maintenance operations. Meanwhile the development of Structural Health Monitoring (SHM) techniques in recent years have demonstrated the potential for this to become a tool that bridge managers can use to optimise inspection and maintenance procedures. This paper reviews recent development in SHM and damage detection techniques. The paper focuses on recent algorithms developed or adapted for damage detection and structural health monitoring in bridge structures, although some of the algorithms presented might be of a more general nature or developed for other kind of structures. The algorithms presented are classified according to the method they use for damage detection and location into Acoustic Emission, Modal Analysis and Statistical pattern recognition based.

This paper presents results from the longitudinal girder displacement and bearing force monitoring on a highway suspension bridge located in Sweden. The monitoring programme was initiated in 2005 by the bridge owner after the discovery of unusual and intense wear in the Teflon layers of the bearings. The initial work focused mainly on a long term monitoring of the bearing forces in the northern abutment. After the first monitoring period of one year the monitoring system was enhanced with a traffic camera, a temperature sensor and accelerometers mounted on the two hangers closest to the instrumented bearing. The monitoring period presented in this paper covers ten months from February to December 2010 and focuses on the horizontal displacement of the girder and on the forces registered in the north-west bearing in conjunction with the traffic information provided by the traffic camera.

The main factors influencing the deterioration of bridges are the environmental conditions and the traffic loads. Hence, a reliable and accurate characterisation of the traffic loads can improve the results from bridge rating, and health bridge monitoring. In this study a Bridge Weigh-in-Motion algorithm is developed to monitor trains passing on a steel railway bridge. The implemented system estimates the traffic loads, speeds and axle spacings. Other valuable information such as peak and RMS vertical bridge deck accelerations are also stored. The system takes advantage of two of the strain gauges from a previously deployed sensor network, installed to mainly monitor the strains for fatigue development. In this paper the possibilities and limitation of this system are explored.