Infrastructure deterioration modeling with an inhomogeneous continuous time Markov chain: A latent state approach with analytic transition probabilities

Daijiro Mizutani, Xian Xun Yuan

研究成果: ジャーナルへの寄稿学術論文査読

3 被引用数 (Scopus)

抄録

Markov chains have been widely used to characterize performance deterioration of infrastructure assets, to model maintenance effectiveness, and to find the optimal intervention strategies. For long-lived assets such as bridges, the time-homogeneity assumptions of Markov chains should be carefully checked. For this purpose, this research proposes a regime-switching continuous-time Markov chain of which the state transition probabilities depend on another, latent, Markov chain that characterizes the overall aging regime of an asset. With the aid of a state-augmentation technique, closed-form solutions for the transition probabilities are analytically derived, making the statistical analysis simple. A case study is presented using the open Ontario Bridge Condition data for provincial highway bridges. The case study demonstrates that the proposed method allows to (1) estimate a statistically superior model to the homogeneous Markov chain and (2) obtain results with comparable accuracy in approximately 48% of the computation time of the state-of-the-art inhomogeneous Markov chain.

本文言語英語
ページ(範囲)1730-1748
ページ数19
ジャーナルComputer-Aided Civil and Infrastructure Engineering
38
13
DOI
出版ステータス出版済み - 2023 9月 1

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