A computing model for quantifying the value of structural health monitoring information in bridge engineering

Abstract

Structural health monitoring system can provide valuable information for improving decision-making process in maintenance and management of bridges. However, managers usually lack understanding of value of structural health monitoring information. This paper developed a computing model for quantifying the value of structural health monitoring information based on Bayesian theory. Then, the model was demonstrated and validated using a simple case and the key factors (i.e., system accuracy, reparation cost, prior probability of structural failure, and manager's behavior pattern) influencing the value of structural health monitoring information were identified and discussed. Findings from this study help to answer the question of whether a structural health monitoring system should be installed and run, thus enriching the knowledge body of structural health monitoring.