The findings of an extensive literature survey focusing on bridge structural health monitoring (SHM) deployments are presented. Conventional, maturing, and emerging technologies are reviewed as well as deployment considerations for new SHM endeavors. The lack of published calibration studies (and quantification of uncertainty studies) for new sensors is highlighted as a major concern and area for future research. There are currently very few examples of SHM systems that have clearly provided significant value to the owners of monitored structures. The results of the literature survey are used to propose a categorization system to better assess the potential outcomes of bridge SHM deployments. It is shown that SHM studies can be categorized as one (or a combination) of the following: (1) anomaly detection, (2) sensor deployment studies, (3) model validation, (4) threshold check, and (5) damage detection. The new framework aids engineers specifying monitoring systems to determine what should be measured and why, hence allowing them to better evaluate what value may be delivered to the relevant stakeholders for the monitoring investments.

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On-going developments in smart technologies such as wireless sensor networks, micro-electro-mechanical systems (MEMS), computer vision, fibre optics and advanced data interpretation techniques may revolutionise structural health monitoring (SHM). Dedicated SHM of bridge assets has the potential to produce valuable data-sets and provide owners and managers with information to aid with key questions such as: current performance, margins of safety, actual loading, stress history and risk of fatigue, extent of deterioration and residual life.However, the parameters measured and value of the data obtained will differ when viewed from the perspectives of different stakeholders such as asset owners, designers, contractors and researchers. In this paper the purposes of monitoring are reviewed. A methodology is proposed to facilitate formal discussions between the key stakeholders before any deployment is specified and to ensure that scarce resources are not wasted in the pursuit of data as opposed to information. This approach can be used to determine if there is a prima facie case for the specification of SHM on a project and assess the potential value of any information that may be obtained. The developed methodology has been trialled with five historical monitoring case studies on bridges with which the authors are familiar.

There has recently been considerable research published on the applicability of monitoring systems for improving civil infrastructure management decisions. Less research has been published on the challenges in interpreting the collected data to provide useful information for engineering decision makers. This paper describes some installed monitoring systems on the Hammersmith Flyover, a major bridge located in central London (United Kingdom). The original goals of the deployments were to evaluate the performance of systems for monitoring prestressing tendon wire breaks and to assess the performance of the bearings supporting the bridge piers because visual inspections had indicated evidence of deterioration in both. This paper aims to show that value can be derived from detailed analysis of measurements from a number of different sensors, including acoustic emission monitors, strain, temperature and displacement gauges. Two structural monitoring systems are described, a wired system installed by a commercial contractor on behalf of the client and a research wireless deployment installed by the University of Cambridge. Careful interpretation of the displacement and temperature gauge data enabled bearings that were not functioning as designed to be identified. The acoustic emission monitoring indicated locations at which rapid deterioration was likely to be occurring; however, it was not possible to verify these results using any of the other sensors installed and hence the only method for confirming these results was by visual inspection. Recommendations for future bridge monitoring projects are made in light of the lessons learned from this monitoring case study.

Visual inspection is the most common form of condition monitoring used by bridge owners. Information derived from visual inspection data is commonly used to indicate the performance of bridge stocks and inform bridge management decisions. However, several studies have highlighted that the inherently subjective nature of the methods used to record this data can result in uncertainty, due to differences between different inspectors' perceptions of the severity and extent of defects. It is important for asset managers to understand the nature of this uncertainty and the implications for decision making. This paper reports the results of a study which compared scoring of bridge defects by pairs of independent inspectors across 200 bridge structures on England's strategic road network. A sample of 200 structures was selected to be representative of Highways England's stock with regard to, inter alia, age, condition and structural form. Routine Principal Inspections for these sample structures, undertaken every six years by the relevant maintaining agents, were also attended by inspectors from WSP Ltd, with defects scored independently by each inspector. The results of these comparisons were used to derive an empirical profile of the uncertainty in different individual defect severity and extent scores. Statistical methods were then used to derive empirical probability density functions for the values of bridge and stock level condition metrics according to the widely adopted Bridge Condition Indicator system. The reported results highlight trends in the reliability of individual defect scores and the impact of uncertainty on commonly used performance metrics.