ABSTRACT

ABSTRACT For infrastructure stakeholders, the use of bridge management systems to manage existing bridge stocks has led to the accumulation of vast databases of condition ratings, primarily gathered through routine visual inspection protocols. Visual inspection is the principal condition assessment method; whereby defined components in the overall bridge structure are inspected and assigned a condition rating from a prescribed scale indicative of the damage state, based on the judgements of a trained inspector. Component level condition rating data can be manipulated in multiple ways to formulate a bridge condition index. The bridge condition index serves as a basis for decision making in relation to implementing maintenance and structural intervention actions in bridge network lifecycle management. The value of visual inspection is contingent on its ability to guide towards optimal decision making in bridge network management and thus is dependent on the accuracy of the bridge condition index used. The worst-conditioned component approach is used to assign an overall condition rating to the structure approximated to the rating of the component in the worst condition, which as a result significantly reduces the overall condition state of a bridge to that of a single component. Multivariate data reduction has been shown to use component-level condition rating data on a large scale to help define information-based, structure-specific weighting factors. This approach estimates the condition rating of the whole structure by combining condition ratings of important bridge components weighted by their significance to the structural integrity of the bridge. This paper considers the effects of multivariate data reduction of condition rating databases on the value of visual inspection. The value of information principle of decision theory is used to establish the difference in cost of a bridge management system decision process implementing both the worst-case condition rating versus the multivariate data reduction technique.