Visual inspection and bridge management

Abstract

This paper estimates visual inspection quantitatively prior to its implementation in a Bridge Management System using a Value of Information (VoI) approach employing a Bayesian pre-posterior analysis. Information from a significant number of real bridges from Ireland and Portugal are considered in this regard following existing commercial practices. The variation of different parameters on the estimated VoI is investigated including the assumed probabilistic models of the prior bridge state, the likelihood of inspector assigned condition ratings and the economic setting surrounding the cost matrix for maintenance decision alternatives. The values of no information, perfect information and imperfect information are presented and the change in the optimal strategy based on such information is assessed. The effect of human imperfections in assessment and difference in condition rating scale are also estimated. The studies and findings of this paper are expected to allow a better insight for practising engineers and researchers working in bridge management.

Keywords:

• Bridge maintenance
• visual inspection
• condition rating
• value engineering
• cost estimates
• decision-making
• Bayesian Networks

Abbreviations:

• Bridge Management System (BMS)
• Value of Information (VoI)
• Value of Perfect Information (VOPI)
• Value of Imperfect Information (VOII)
• Bayesian Network (BN)
• Influence Diagram (ID)
• Maximum Expected Utility (MEU)
• Limited Memory Influence Diagram (LIMID)
• Decision Maker (DM)

Acknowledgements

Thanks to Mr John Lapthorne of Cork County Council and Infraestruturas de Portugal for providing support and aggregated data for this research. This article is based upon work from COST Action TU1406 Quality Specifications for Roadway Bridges, Standardization at a European Level, supported by COST (European Cooperation in Science and Technology).