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路面抗滑性能检测与预估方法综述

谭忆秋 肖神清 熊学堂

谭忆秋, 肖神清, 熊学堂. 路面抗滑性能检测与预估方法综述[J]. 交通运输工程学报, 2021, 21(4): 32-47. doi: 10.19818/j.cnki.1671-1637.2021.04.002
引用本文: 谭忆秋, 肖神清, 熊学堂. 路面抗滑性能检测与预估方法综述[J]. 交通运输工程学报, 2021, 21(4): 32-47. doi: 10.19818/j.cnki.1671-1637.2021.04.002
TAN Yi-qiu, XIAO Shen-qing, XIONG Xue-tang. Review on detection and prediction methods for pavement skid resistance[J]. Journal of Traffic and Transportation Engineering, 2021, 21(4): 32-47. doi: 10.19818/j.cnki.1671-1637.2021.04.002
Citation: TAN Yi-qiu, XIAO Shen-qing, XIONG Xue-tang. Review on detection and prediction methods for pavement skid resistance[J]. Journal of Traffic and Transportation Engineering, 2021, 21(4): 32-47. doi: 10.19818/j.cnki.1671-1637.2021.04.002

路面抗滑性能检测与预估方法综述

doi: 10.19818/j.cnki.1671-1637.2021.04.002
基金项目: 

国家自然科学基金项目 U20A20315

国家重点研发计划项目 2016YFE0202400

详细信息
    作者简介:

    谭忆秋(1968-),女,吉林德惠人,哈尔滨工业大学教授,工学博士,从事道路材料功能特性与应用研究研究

  • 中图分类号: U416.217

Review on detection and prediction methods for pavement skid resistance

Funds: 

National Natural Science Foundation of China U20A20315

National Key Research and Development Program of China 2016YFE0202400

More Information
  • 摘要: 针对道路工程中路面抗滑性能检测与预估中存在的问题,分别从力学机理、检测方法、预估模型3个方面系统梳理了路面抗滑性能相关成果及进展;基于传统的库伦摩擦定律,阐明了路面抗滑性能的摩擦力学机理,从路面、轮胎以及接触环境3个方面总结了抗滑性能的影响因素;总结了抗滑性能的直接与间接测量方法,重点分析了路表纹理检测技术的难点以及测试数据的预处理方法;对比分析了抗滑性能预估的传统经验统计模型、力学模型以及机器学习等方法的优点与不足。研究结果表明:影响路面抗滑性能的因素众多,传统的摩擦理论难以描述橡胶与粗糙表面接触界面第三体的力学行为,因此,需要进一步研究具有润滑介质的接触界面摩擦机理;抗滑性能直接检测方法功能单一,成本较高,表面纹理的高速无接触自动化检测更加符合未来智能一体化检测需求,但高精度、大量程检测以及数据清洗仍是需要突破的瓶颈;相比现行的各类预估模型,经验统计模型及机器学习弱化了胎-路接触特性,导致预估模型缺乏扩展性;推行有限元仿真力学模型方法,有望进一步揭示复杂物理场下的摩擦机理,从而开发更精准、高效的路面抗滑预估模型。

     

  • 图  1  不同滑移率下轮胎的附着系数

    Figure  1.  Adhesion coefficients under different slip ratios of tire

    图  2  胎-路摩擦机理

    Figure  2.  Tire-pavement friction mechanism

    图  3  抗滑性能影响因素

    Figure  3.  Influencing factors of skid resistance

    图  4  路表状态高速自动检测系统

    Figure  4.  High-speed automatic detection system of road surface condition

    图  5  路表纹理激光检测

    Figure  5.  Road surface texture laser detection

    图  6  足尺环道横向摩擦因数与平均断面深度

    Figure  6.  SFC and MPD of full-scale track

    图  7  横向摩擦因数与平均断面深度的关系

    Figure  7.  Relationship between SFC and MPD

    图  8  基于路表纹理的抗滑性能预估方法

    Figure  8.  Prediction methods of skid resistance performance based on pavement surface texture

    图  9  轮胎-流体-路面有限元模型

    Figure  9.  Finite element model of tire-fluid-pavement

    图  10  橡胶粗糙表面多尺度接触

    Figure  10.  Multi-scale contact between rubber and rough surface

    图  11  人工智能方法及深度学习框架

    Figure  11.  Artificial intelligence methods and deep learning framework

    图  12  卷积神经网络基本框架及运算示意

    Figure  12.  Basic framework and operation illustration of CNN

    图  13  摩擦因数的残差网络结构

    Figure  13.  Structure of friction-residual networks

    表  1  路面抗滑性能检测方法

    Table  1.   Pavement skid resistance test methods

    检测方式 检测方法 代表性装置 检测特点 文献、规范标准
    直接测量 横向力检测 英国Mu-Meter、SCRIM 检测速度为64 km·h-1; 喷水速率为1.2 L·min-1;数据采集为25~125 mm·次-1,以1 m间隔;适用于直线路段、曲线和陡坡路段。 ASTM E 670
    (锁轮)纵向力检测 美国Trailer 检测速度为64 km·h-1; 水膜厚度为0.5 mm; 数据采集为完全锁定后1~3 s取均值;适用于直线路段。 ASTM E 274
    固定滑移率 英国Grip Tester、芬兰BV-11 滑移率为12%~ 20%;喷水速率为1.2 L·min-1; 数据采集为25~125 mm·次-1,以1 m间隔平均;适用于直线路段。 ASTM E 1844
    可变滑移率 法国IMAG、挪威RUNAR 滑移率为0~100%;水膜厚度为0.5 mm;数据采集间距小于2.5 mm;适用于直线路段、曲线和陡坡路段。 ASTM E 1859
    小型移动式摩擦测试仪 步行式摩擦测试仪(Walking Friction Tester, WFT) 检测方式为人工手推;喷水速率为45 mL·min-1;接触压力为99.2 kPa;适用于室内或现场。 [24]
    旋转摩擦因数检测 动态摩擦因数仪(Dynamic Friction Tester, DFT) 检测速度为5~89 km·h-1;喷水速率为3.6 L·min-1;适用于室内及现场。 ASTM E 1911
    摆式摩擦因数检测 英式摆锤(British Pendulum Tester, BPT) 检测速度为10 km·h-1;适用于室内及现场。 ASTM E 303
    刹车距离测量 客车或轻型卡车 检测速度为64 km·h-1;适用于直线路段。 ASTM E 445
    减速度测量 加速度计 检测速度为32~48 km·h-1;适用于直线路段。 ASTM E 2101
    间接测量 铺沙法 铺沙仪 通过相关特征参数来表征路表的抗滑性能,如平均构造深度。 ASTM E 965、ISO 10844
    排水法 路面渗水仪 ASTM E 2380
    表面纹理 激光扫描仪 ASTM E 2157、ASTM E 1845、ISO 13473
    其他方法 力/声/温度传感器 [25]~[27]
    下载: 导出CSV
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  • 收稿日期:  2021-03-15
  • 网络出版日期:  2021-09-16
  • 刊出日期:  2021-08-01

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