Preliminary study on bridge health prediction using Dynamic Objective Oriented Bayesian Network (DOOBN)

Wang, Ruizi, Ma, Lin, Yan, Cheng, & Mathew, Joseph (2010) Preliminary study on bridge health prediction using Dynamic Objective Oriented Bayesian Network (DOOBN). In Proceedings of : WCEAM 2010 : Fifth World Congress on Engineering Asset Management, World Congress on Engineering Asset Management, Brisbane, Qld..

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The availability of bridges is crucial to people’s daily life and national economy. Bridge health prediction plays an important role in bridge management because maintenance optimization is implemented based on prediction results of bridge deterioration. Conventional bridge deterioration models can be categorised into two groups, namely condition states models and structural reliability models. Optimal maintenance strategy should be carried out based on both condition states and structural reliability of a bridge. However, none of existing deterioration models considers both condition states and structural reliability. This study thus proposes a Dynamic Objective Oriented Bayesian Network (DOOBN) based method to overcome the limitations of the existing methods. This methodology has the ability to act upon as a flexible unifying tool, which can integrate a variety of approaches and information for better bridge deterioration prediction. Two demonstrative case studies are conducted to preliminarily justify the feasibility of the methodology

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ID Code: 47717
Item Type: Conference Paper
Refereed: Yes
Keywords: Bridge health prediction, Dynamic object oriented Bayesian network (DOOBN), Condition States, Structural reliability
Subjects: Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > CIVIL ENGINEERING (090500) > Infrastructure Engineering and Asset Management (090505)
Divisions: Current > Research Centres > CRC Integrated Engineering Asset Management (CIEAM)
Past > QUT Faculties & Divisions > Faculty of Built Environment and Engineering
Past > Schools > School of Engineering Systems
Copyright Owner: Copyright 2010 please consult the authors
Deposited On: 14 Dec 2011 00:27
Last Modified: 14 Dec 2011 00:29

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