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一种用于预测民用机场刚性道面剩余使用寿命的马尔可夫概率模型的创新

An Innovation of the Markov Probability Model for Predicting the Remaining Service Life of Civil Airport Rigid Pavements.

作者信息

Wei Baoli, Guo Chengchao, Deng Miaoyi

机构信息

School of Civil Engineering and Architecture, Zhengzhou University of Aeronautics, Zhengzhou 450046, China.

School of Civil Engineering, Sun Yat-sen University, Zhuhai 519082, China.

出版信息

Materials (Basel). 2022 Sep 2;15(17):6082. doi: 10.3390/ma15176082.

DOI:10.3390/ma15176082
PMID:36079463
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9457356/
Abstract

In view of the time series update of airport runway health status detection data, the Markov chain of stochastic process theory was adopted. Considering the influence of aircraft traffic load, age, and pavement structure surface-layer thickness on the performance deterioration process of airport runways, the method of survival analysis was used. The parameter model of survival analysis was used to establish the duration function model of the four condition states of the airport runway PCI (pavement condition index). The Markov transition matrix for the performance prediction of airport runways was constructed. In order to evaluate the ability of the Markov transition matrix method to predict the trend of deterioration for PCI of the airport runway under different conditions of aircraft traffic volume and thickness of the runway pavement surface, a data set was constructed with the actual inspection data of the airport runway, and the corresponding samples were selected for analysis. The results showed that a Markov transition matrix for airport runway performance prediction, constructed based on survival analysis theory, can combine discontinuous inspection data or monitoring data with Weibull function survival curves. The method proposed in this paper can quantitatively predict the remaining service life of airport runways and provide support for cost-effective decisions about airport pavement maintenance and rehabilitation.

摘要

针对机场跑道健康状况检测数据的时间序列更新,采用了随机过程理论中的马尔可夫链。考虑到飞机交通荷载、使用年限以及道面结构面层厚度对机场跑道性能劣化过程的影响,运用了生存分析方法。利用生存分析的参数模型建立了机场跑道路面状况指数(PCI)四种状态的持续时间函数模型。构建了用于机场跑道性能预测的马尔可夫转移矩阵。为评估马尔可夫转移矩阵方法在不同飞机交通量和跑道道面厚度条件下预测机场跑道PCI劣化趋势的能力,利用机场跑道实际检测数据构建数据集,并选取相应样本进行分析。结果表明,基于生存分析理论构建的用于机场跑道性能预测的马尔可夫转移矩阵,能够将不连续的检测数据或监测数据与威布尔函数生存曲线相结合。本文提出的方法能够定量预测机场跑道的剩余使用寿命,为机场道面养护与修复的成本效益决策提供支持。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/531a/9457356/21e36172a93a/materials-15-06082-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/531a/9457356/f47a5b664d83/materials-15-06082-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/531a/9457356/1c41fcdd6522/materials-15-06082-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/531a/9457356/2cd392f7ae23/materials-15-06082-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/531a/9457356/8caec2322946/materials-15-06082-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/531a/9457356/76ef9e05b9d6/materials-15-06082-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/531a/9457356/6b61953a0353/materials-15-06082-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/531a/9457356/4de1ab0a50ff/materials-15-06082-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/531a/9457356/21e36172a93a/materials-15-06082-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/531a/9457356/f47a5b664d83/materials-15-06082-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/531a/9457356/1c41fcdd6522/materials-15-06082-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/531a/9457356/2cd392f7ae23/materials-15-06082-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/531a/9457356/8caec2322946/materials-15-06082-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/531a/9457356/76ef9e05b9d6/materials-15-06082-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/531a/9457356/6b61953a0353/materials-15-06082-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/531a/9457356/4de1ab0a50ff/materials-15-06082-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/531a/9457356/21e36172a93a/materials-15-06082-g008.jpg

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本文引用的文献

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