Reconstruction and evolution of 3D model on asphalt pavement surface texture using digital image processing technology and accelerated pavement testing

被引:1
|
作者
Ji, XiaoPing [1 ]
Zhu, Shiyu [1 ]
Sun, Yunlong [2 ]
Li, Hangle [3 ]
Chen, Ye [1 ]
Chen, Yun [1 ]
机构
[1] Changan Univ, Key Lab Special Area Highway Engn, Minist Educ, Xian, Shaanxi, Peoples R China
[2] Xinjiang Transportat Planning Surveying & Design I, Urumqi, Xinjiang, Peoples R China
[3] Tian Jin Municipal Engn Design & Res Inst Co Ltd, Shenzhen, Guangdong, Peoples R China
基金
中国国家自然科学基金;
关键词
Asphalt pavement; surface texture; digital image processing technology; accelerated pavement testing; evolutionary characteristics; SKID-RESISTANCE;
D O I
10.1080/14680629.2023.2268750
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Asphalt pavement surface texture is the main factor affecting pavement function. Reconstruction of the asphalt pavement surface texture is needed to accurately reveal its evolutionary characteristics for pavement performance and quality evaluation. To reconstruct an optimised 3D model of the asphalt pavement surface texture and to study its evolutionary properties, digital image processing technique and accelerated pavement testing system were used. First, the asphalt pavement surface texture 3D model optimised by three camera parameters and their thresholds. Next, the accelerated pavement testing system simulated traffic loadings on dense-gradation asphalt mixtures to investigate the pavement surface texture evolution properties. Finally, predictive models are developed for the asphalt pavement surface texture evolution. Results show that the optimised pavement texture 3D model resembles actual pavement structure. The surface texture evolutionary characteristics of asphalt pavement can be divided into three periods and six stages. The evolution model can accurately characterise the evolution of the surface texture of asphalt pavement.Abbreviations: MLS11: Accelerated pavement testing system; HP: Mean pixel difference; Df: Fractal Dimension; MTD: Mean Texture Depth; BPN: British Pendulum Number
引用
收藏
页码:1694 / 1719
页数:26
相关论文
共 50 条
  • [31] Feasibility study of asphalt pavement pothole properties measurement using 3D line laser technology
    Xin, She
    Zhang, Hongwei
    Zhou, Wang
    Jiao, Yan
    INTERNATIONAL JOURNAL OF TRANSPORTATION SCIENCE AND TECHNOLOGY, 2021, 10 (01) : 83 - 92
  • [32] Quality Assessment of Milling Pavement Surface Using 3D Line Laser Technology
    Hui, Bing
    Guo, Mu
    Liu, Xiaofang
    JOURNAL OF SENSORS, 2018, 2018
  • [33] Automatically detect and classify asphalt pavement raveling severity using 3D technology and machine learning
    Yi-Chang (James) Tsai
    Yipu Zhao
    Bruno Pop-Stefanov
    Anirban Chatterjee
    International Journal of Pavement Research and Technology, 2021, 14 : 487 - 495
  • [34] Automatically detect and classify asphalt pavement raveling severity using 3D technology and machine learning
    Tsai, Yi-Chang
    Zhao, Yipu
    Pop-Stefanov, Bruno
    Chatterjee, Anirban
    INTERNATIONAL JOURNAL OF PAVEMENT RESEARCH AND TECHNOLOGY, 2021, 14 (04) : 487 - 495
  • [35] Stereo-vision applications to reconstruct the 3D texture of pavement surface
    El Gendy, Amin
    Shalaby, Ahmed
    Saleh, Mohamed
    Flintsch, Gerardo W.
    INTERNATIONAL JOURNAL OF PAVEMENT ENGINEERING, 2011, 12 (03) : 263 - 273
  • [36] Research on water seepage detection technology of tunnel asphalt pavement based on deep learning and digital image processing
    Li, Jiaqi
    He, Zhaoyi
    Li, Dongxue
    Zheng, Aichen
    SCIENTIFIC REPORTS, 2022, 12 (01)
  • [37] Automatic pavement texture measurement using a new 3D image-based profiling system
    Mataei, Behrouz
    Nejad, Fereidoon Moghadas
    Zakeri, Hamzeh
    MEASUREMENT, 2022, 199
  • [38] Research on water seepage detection technology of tunnel asphalt pavement based on deep learning and digital image processing
    Jiaqi Li
    Zhaoyi He
    Dongxue Li
    Aichen Zheng
    Scientific Reports, 12
  • [39] METHODS OF 3D RECONSTRUCTION USING DIGITAL IMAGE-PROCESSING
    ALFF, M
    EUROPEAN JOURNAL OF CELL BIOLOGY, 1987, 44 : 2 - 2
  • [40] Quantitative Analysis of Macrotexture of Asphalt Concrete Pavement Surface Based on 3D Data
    Ju, Huyan
    Li, Wei
    Tighe, Susan
    Sun, Zhaoyun
    Sun, Hongchao
    TRANSPORTATION RESEARCH RECORD, 2020, 2674 (08) : 732 - 744