Optimal intervention strategies for multiple objects affected by manifest and latent deterioration processes
Optimal intervention strategies for multiple objects affected by manifest and latent deterioration processes
复制标题
针对受明显和潜在恶化过程影响的多个对象的最佳干预策略
DOI：
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发表时间：
2015
期刊：
影响因子：
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通讯作者：
D. Fernando
中科院分区：
文献类型：
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作者：
Nam Lethanh;B. Adey;D. Fernando
在现有的基础设施管理系统中，最优干预策略（OIS）是针对逐渐恶化的对象（明显恶化过程，MDP）确定的，假设通过适当的检查和干预策略，对象的故障概率可以忽略不计。不考虑突然恶化的对象（潜在恶化过程，LDPs），例如，由于洪水期间的冲刷或地震期间的地壳运动。由于MDP和LDP两者而劣化的对象的OIS的确定需要考虑两者。然而，后者意味着必须考虑对象的故障概率。在这篇文章中，马尔可夫模型，可用于确定受不相关的MDP和LDP的影响的多个对象的多种类型的OIS。该模型是马耶和Madanat提出的模型的扩展（桥梁管理系统中的抗震考虑。计算机辅助土木和基础设施工程，17：185 - 193，2002）。在该模型中，一组条件状态（CS）被用来描述每种类型的对象的条件，其中每个集合由非故障CS和故障CS组成。从每个非故障CS到每个故障CS的概率使用归一化的脆弱性曲线来估计，并且从每个非故障CS到每个非故障CS的概率使用小林、凯托和勒桑的马尔可夫劣化预测模型（一种贝叶斯估计方法，以改进具有马尔可夫链模型的基础设施系统的劣化预测）来初始估计。International Journal of Architecture，Engineering and Construction，1：1 - 13，2012 a），并在考虑进入失败CS的概率后进行了调整。该模型的使用演示使用的道路连接，包括一个路段和一座桥梁。
In the existing infrastructure management systems, optimal interventions strategies (OISs) are determined for objects that deteriorate gradually (manifest deterioration process, MDPs), under the assumption that with appropriate inspection and intervention strategies the probability of failure of object can be neglected. Objects that deteriorate suddenly (latent deterioration process, LDPs), for example, due to scouring during a flood or earth movements during an earthquake are not considered. The determination of OISs for an object that deteriorates due to both MDPs and LDPs requires the consideration of both. The latter, however, means that the probability of failure of the object must be considered. In this article, a Markov model is presented that can be used to determine OISs for multiple objects of multiple types affected by uncorrelated MDPs and LDPs. The model is an extension of the model proposed by Mayet and Madanat (Incorporation of seismic considerations in bridge management systems. Computer-Aided Civil and Infrastructure Engineering, 17:185–193, 2002). In the model, a set of condition states (CSs) is used to describe the condition of objects of each type, where each set is composed of non-failure CSs and failure CSs. The probabilities of going from each non-failure CS to each failure CS are estimated using normalised fragility curves, and the probabilities of going from each non-failure CS to each non-failure CS are initially estimated using the Markov deterioration prediction model of Kobayashi, Kaito, and Lethanh (A Bayesian estimation method to improve deterioration prediction for infrastructure system with Markov chain model. International Journal of Architecture, Engineering and Construction, 1:1–13, 2012a) and later adjusted taking into consideration the probabilities of entering the failure CSs. The use of the model is demonstrated using a road link comprising one road section and one bridge.