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Comparison between the predicted performance curve and the Markov Chain models for structural performance of infrastructure components

机译:预测性能曲线与马尔可夫链模型在基础设施组件结构性能方面的比较

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This paper compares the PPC model to a Markov Chain (MC) stochastic deterioration model. First, inspection data from the Société de Transport de Montréal (STM) is gathered and analyzed. Then Transition Probability Matrices (TPM) are developed, and, using Matlab, MC deterioration curves are developed. Comparison between MC and the PPC deterioration curves is performed for subway station walls and slabs. The comparison has shown that the useful service life can be as low as 2 years for components having many inspection history records, and very high as 30 years for components having very few inspection history records. The PPC model has always a higher useful service life estimate. Also, the MC has a ten times higher deterioration rate (0.2 per year) compared to the PPC model (0.02 per year). It can be concluded that the MC deterioration model requires a high amount of inspection data, and it is mathematically difficult to generate since most practicing managers and engineers have no background in Markov Chain modeling.
机译:本文将PPC模型与马尔可夫链(MC)随机恶化模型进行了比较。首先,收集并分析来自蒙特利尔交通运输局(STM)的检查数据。然后开发过渡概率矩阵(TPM),并使用Matlab绘制MC劣化曲线。对地铁站墙和楼板进行了MC和PPC劣化曲线之间的比较。比较表明,对于具有许多检查历史记录的组件,使用寿命可以低至2年,对于具有很少检查历史记录的组件,使用寿命可以高达30年。 PPC模型始终具有较高的使用寿命估计。而且,MC的退化率(每年0.2)是PPC模型(每年0.02)的十倍。可以得出结论,MC恶化模型需要大量的检验数据,并且由于大多数从业经理和工程师都没有马尔可夫链建模的背景,因此在数学上很难生成。

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