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Bridge Deterioration Prediction Model Based On Hybrid Markov-System Dynamic

机译:基于Hybrid Markov-系统动态的桥梁劣化预测模型

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Instantaneous bridge failure tends to increase in Indonesia. To mitigate this condition, Indonesia’s Bridge Management System (I-BMS) has been applied to continuously monitor the condition of bridges. However, I-BMS only implements visual inspection for maintenance priority of the bridge structure component instead of bridge structure system. This paper proposes a new bridge failure prediction model based on hybrid Markov-System Dynamic (MSD). System dynamic is used to represent the correlation among bridge structure components while Markov chain is used to calculate temporal probability of the bridge failure. Around 235 data of bridges in Indonesia were collected from Directorate of Bridge the Ministry of Public Works and Housing for calculating transition probability of the model. To validate the model, a medium span concrete bridge was used as a case study. The result shows that the proposed model can accurately predict the bridge condition. Besides predicting the probability of the bridge failure, this model can also be used as an early warning system for bridge monitoring activity.
机译:瞬时桥梁失败往往会增加印度尼西亚。为了减轻这种情况,印度尼西亚的桥梁管理系统(I-BMS)已被应用于连续监控桥梁的状况。然而,I-BMS仅实现了用于桥接结构组件的维护优先级而不是桥接结构系统的视觉检查。本文提出了一种基于Hybrid Markov系统动态(MSD)的新桥梁故障预测模型。系统动态用于表示桥接结构组件之间的相关性,而马尔可夫链用于计算桥梁故障的时间概率。在公共工程部和房屋内收集了印度尼西亚的桥梁大约235个数据,以计算模型的转型概率。为了验证模型,使用中跨度混凝土桥作为案例研究。结果表明,所提出的模型可以准确地预测桥接条件。除了预测桥梁故障的概率外,该模型还可以用作桥梁监测活动的预警系统。

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