交通运输系统工程与信息

交通运输系统工程与信息 ›› 2021, Vol. 21 ›› Issue (3): 247-253.

• 系统工程理论与方法 • 上一篇    下一篇

基于数据驱动的机场水泥混凝土道面性能退化预测

魏保立*1，2，郭成超3，邓苗毅2   

  1. 1. 郑州大学，水利科学与工程学院，郑州 450001；2. 郑州航空工业管理学院，土木建筑学院，郑州 450046； 3. 中山大学，土木工程学院，广东 珠海 519082
  • 收稿日期:2021-04-06 修回日期:2021-05-17 出版日期:2021-06-25 发布日期:2021-06-25
  • 作者简介:魏保立(1978- )，男，河南郾城人，讲师，博士生。
  • 基金资助:

    河南省高等学校重点科研项目/ Key Research Program of the Higher Education Institutions of Henan Province, China (21B580008)；国家重点研发计划/National Key Research and Development Program of China (2016YFC0802203-5)；河南省科技攻关项目/Science and Technology Program of Henan Province (182102310747)。

Predicting Performance Degradation for Airport Portland Cement Concrete Pavements Based on Data-driven

WEI Bao-li* 1, 2，GUOCheng-chao3，DENG Miao-yi2   

  1. 1. School of Water Conservancy and Environment, Zhengzhou University, Zhengzhou 450001, China; 2. School of Civil and Architecture, Zhengzhou University of Aeronautics, Zhengzhou 450046, China; 3. School of Civil Engineering, Sun Yat-sen University, Zhuhai 519082, Guangdong, China
  • Received:2021-04-06 Revised:2021-05-17 Online:2021-06-25 Published:2021-06-25

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摘要：

针对机场道面性能退化过程的精确预测问题，本文采用数据驱动的机场道面预测性维护方法，通过指示变量将两种数据集进行联合分析，考虑机场道面性能退化过程受飞行交通量和道面面层厚度的影响，以机场道面性能状况指数衰变的非线性函数为期望函数，建立一种机场道面性能退化双参数预测模型；根据模型的参数估计结果，采用边际效应分析结合预测性能曲线图示，对不同飞行交通量水平和不同道面厚度等级的道面性能退化过程预测进行分析。结果表明，采用数据驱动和非线性混合效应方法，搭载联合估计技术，能较为显著地提高机场道面性能退化预测的精度和效果。

关键词: 航空运输, 混合效应模型, 数据驱动, 机场水泥混凝土道面, 性能退化

Abstract:

In order to accurately predict the airport pavement performance degradation, this paper adopts a data-driven predictive maintenance method, analyzes two data sets by means of indicator variables, considers the influence of flight traffic volume and pavement surface thickness, and establishes a two-parameter prediction model for airport pavement performance degradation with taking the nonlinear function of decay of airport PCI(pavement condition index) as the expectation function. Based on the parameter estimation results of the model, a marginal effect analysis combined with the predicted performance curve is used to analyze the prediction of the degradation under different flight traffic levels and different pavement surface thickness classes. The results show that the data-driven method and nonlinear mixedeffects approach with the joint estimation technique can significantly improve the accuracy and effectiveness of airport pavement performance degradation prediction.

Key words: air transportation, mixed-effects model, data-driven, airport portland cement concrete pavements, performance degradation

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