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《工程(英文)》 >> 2021年 第7卷 第6期 doi: 10.1016/j.eng.2020.07.030

埋入式传感、图像处理技术和机器学习方法在路面监测与分析中应用的最新研究进展

a Beijing Key Laboratory of Traffic Engineering, Beijing University of Technology, Beijing 100124, China
b Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport, Beijing Jiaotong University, Beijing 100044, China
c Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hong Kong 999077, China
d National Center for Materials Service Safety, University of Science and Technology Beijing, Beijing 100083, China
e School of Transportation, Southeast University, Nanjing 211189, China
f Department of Civil and Environmental Engineering, Virginia Tech, Blacksburg, VA 24061, USA

收稿日期: 2020-05-10 修回日期: 2020-07-05 录用日期: 2020-07-24 发布日期: 2021-12-29

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摘要

在现代交通系统中,道路作为车辆和行人使用频率最高的民用基础设施之一,其服役状况和使用寿命直接影响通行体验和效率。因此,在路面发生不可逆损伤之前进行路面健康监测和及时养护,对于保障公共交通服务质量以及通行安全至关重要。通过路面结构动力响应监测和路面状况评估可有效表征路面损伤状况。埋入式传感器、图像处理和机器学习是目前常用的三种路面结构动力响应监测技术和分析方法。本文综述了近年来上述三种技术在路面工程中的应用现状,并阐述了这些技术在未来路面工程监测与分析中的发展方向。

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