留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码
马建, 赵祥模, 贺拴海, 宋宏勋, 赵煜, 宋焕生, 程磊, 王建锋, 袁卓亚, 黄福伟, 张健, 杨澜. 路面检测技术综述[J]. 交通运输工程学报, 2017, 17(5): 121-137.
引用本文: 马建, 赵祥模, 贺拴海, 宋宏勋, 赵煜, 宋焕生, 程磊, 王建锋, 袁卓亚, 黄福伟, 张健, 杨澜. 路面检测技术综述[J]. 交通运输工程学报, 2017, 17(5): 121-137.
MA Jian, ZHAO Xiang-mo, HE Shuan-hai, SONG Hong-xun, ZHAO Yu, SONG Huan-sheng, CHENG Lei, WANG Jian-feng, YUAN Zhuo-ya, HUANG Fu-wei, ZHANG Jian, YANG Lan. Review of pavement detection technology[J]. Journal of Traffic and Transportation Engineering, 2017, 17(5): 121-137.
Citation: MA Jian, ZHAO Xiang-mo, HE Shuan-hai, SONG Hong-xun, ZHAO Yu, SONG Huan-sheng, CHENG Lei, WANG Jian-feng, YUAN Zhuo-ya, HUANG Fu-wei, ZHANG Jian, YANG Lan. Review of pavement detection technology[J]. Journal of Traffic and Transportation Engineering, 2017, 17(5): 121-137.

路面检测技术综述

基金项目: 

高等学校学科创新引智计划项目 B14043

国家重点研发计划项目 2017YFCO804800

陕西省重点研发计划项目 2017ZDXM-SF-091

详细信息
    作者简介:

    马建(1957-), 男, 陕西西安人, 长安大学教授, 工学博士, 从事交通运输研究

  • 中图分类号: U416.2

Review of pavement detection technology

More Information
  • 摘要: 总结了路面检测重要研究成果, 分析了路面损坏、平整度、车辙、抗滑性能(构造深度) 和结构强度(弯沉) 检测技术的发展现状, 研究了路面检测技术的不足与发展方向。研究结果表明: 国内外路面检测技术的发展经历了3个阶段, 从早期传统的人工检测到20世纪末的半自动化检测, 发展到目前的无损自动检测; 无损自动检测的主要特点是快速与智能化, 采用多源传感器协同工作, 并且集成在多功能道路检测车上, 能够同时检测路面损坏、平整度、车辙、抗滑性能和结构强度以及道路线形与沿线设施等; 在路面损坏检测方面, 采用数字图像检测技术, 实现了路面裂缝的快速检测; 在路面平整度检测方面, 采用激光位移传感技术, 实现了快速自动化检测; 在路面车辙检测方面, 采用激光和数字图像技术, 实现了非接触智能化检测; 在路面抗滑性能和结构强度检测方面, 建立了铺砂法与贝克曼梁法检测结果的相关关系, 实现了基于激光技术的路面构造深度与弯沉快速检测; 为了减少外界因素对现有检测技术和检测设备的干扰, 提高检测信号的信噪比, 应该开发适合各种工况下的路面检测和数据处理方法, 实现路面检测高效化与智能化。

     

  • [1] MOHAN A, POOBAL S. Crack detection using image processing: a critical review and analysis[J]. Alexandria Engineering Journal, 2017, DOI: 10.1016/j.aej.2017.01.020.
    [2] JIANG Ming-hu, GIELEN G, DENG Bei-xing, et al. A fast learning algorithm for time-delay neural networks[J]. Information Sciences, 2002, 148 (1-4): 27-39. doi: 10.1016/S0020-0255(02)00273-6
    [3] 啜二勇. 国外路面自动检测系统发展综述[J]. 交通标准化, 2009 (204): 96-99. https://www.cnki.com.cn/Article/CJFDTOTAL-JTBH200917028.htm

    CHUO Er-yong. Development summary of international pavement surface distress automatic survey system[J]. Transport Standardization, 2009 (204): 96-99. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-JTBH200917028.htm
    [4] KIM J Y. Development of new automated crack measurement algorithm using laser images of pavement surface[D]. Iowa: The University of Iowa, 2008.
    [5] MONEM T A, OLOUFA A A, MAHGOUB H. Asphalt crack detection using thermography[R]. Orlando: University of Central Florida, 2005: 1-12.
    [6] WANG K C P. Elements of automated survey of pavements and a3Dmethodology[J]. Journal of Modern Transportation, 2011, 19 (1): 51-57. doi: 10.1007/BF03325740
    [7] WANG K C P, GONG Wei-guo. Real-time automated survey system of pavement cracking in parallel environment[J]. Journal of Infrastructure Systems, 2005, 11 (3): 154-164. doi: 10.1061/(ASCE)1076-0342(2005)11:3(154)
    [8] HUANG Ya-xiong, XU Bu-gao. Automatic inspection of pavement cracking distress[J]. Journal of Electronic Imaging, 2006, 15 (1), DOI: 10.1117/1.2177650.
    [9] CHENG H D, MIYOJIM M. Automatic pavement distress detection system[J]. Information Sciences, 1998, 108 (1-4): 219-240. doi: 10.1016/S0020-0255(97)10062-7
    [10] 王建锋. 激光路面三维检测专用车技术与理论研究[D]. 西安: 长安大学, 2010.

    WANG Jian-feng. Research on vehicle technology on road three-dimension measurement[D]. Xi'an: Chang'an University, 2010. (in Chinese).
    [11] 罗瑞. 基于图像处理的路面裂缝检测算法研究[D]. 芜湖: 安徽工程大学, 2017.

    LUO Rui. Research of pavement crack detection algorithm based on image process[D]. Wuhu: Anhui Polytechnic University, 2017. (in Chinese).
    [12] CHENG Heng-da, CHEN Jim-rong, GLAZIER C, et al. Anovel fuzzy logic approach to pavement distress detection[C]//SPIE. Nondestructive Evaluation of Bridges and Highways. Breda: SPIE, 1996: 97-108.
    [13] BHUTANI K R, BATTOU A. Application of fuzzy relations to image enhancement[J]. Pattern Recognition Letters, 1995, 16 (9): 901-909. doi: 10.1016/0167-8655(95)00035-F
    [14] 刘玉臣, 王国强, 林建荣. 基于模糊理论的路面裂缝图像增强方法[J]. 筑路机械与施工机械化, 2006 (2): 35-37. doi: 10.3969/j.issn.1000-033X.2006.02.016

    LIU Yu-chen, WANG Guo-qiang, LIN Jian-rong. Image enhancement for pavement crack image based on fuzzy theory[J]. Road Machinery and Construction Mechanization, 2006 (2): 35-37. (in Chinese). doi: 10.3969/j.issn.1000-033X.2006.02.016
    [15] 唐磊, 赵春霞, 王鸿南, 等. 路面图像增强的多偏微分方程融合法[J]. 中国图象图形学报, 2008, 13 (9): 1661-1666. https://www.cnki.com.cn/Article/CJFDTOTAL-ZGTB200809005.htm

    TANG Lei, ZHAO Chun-xia, WANG Hong-nan, et al. Fusion of multiple basic PDE models for enhancing road surface images[J]. Journal of Image and Graphics, 2008, 13 (9): 1661-1666. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-ZGTB200809005.htm
    [16] ZUO Yong-xia, WANG Guo-qiang, ZUO Chun-cheng. Wavelet packet denoising for pavement surface cracks detection[C]//IEEE. International Conference on Computational Intelligence and Security. New York: IEEE, 2008: 481-484.
    [17] ZHANG Da-qi, QU Shi-ru, HE Li, et al. Automatic ridgelet image enhancement algorithm for road crack image based on fuzzy entropy and fuzzy divergence[J]. Optics and Lasers in Engineering, 2009, 47 (11): 1216-1225. doi: 10.1016/j.optlaseng.2009.05.014
    [18] 王兴建, 秦国锋, 赵慧丽. 基于多级去噪模型的路面裂缝检测方法[J]. 计算机应用, 2010, 30 (6): 1606-1609, 1612. https://www.cnki.com.cn/Article/CJFDTOTAL-JSJY201006051.htm

    WANG Xing-jian, QIN Guo-feng, ZHAO Hui-li. Pavement crack detection method based on multilevel denoising model[J]. Journal of Computer Applications, 2010, 30 (6): 1606-1609, 1612. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-JSJY201006051.htm
    [19] 李清泉, 胡庆武. 基于图像自动匀光的路面裂缝图像分析方法[J]. 公路交通科技, 2010, 27 (4): 1-5, 27. doi: 10.3969/j.issn.1002-0268.2010.04.001

    LI Qing-quan, HU Qing-wu. A pavement crack image analysis approach based on automatic image dodging[J]. Journal of Highway and Transportation Research and Development, 2010, 27 (4): 1-5, 27. (in Chinese). doi: 10.3969/j.issn.1002-0268.2010.04.001
    [20] KIRSCHKE K R, VELINSKY S A. Histogram-based approach for automated pavement-crack sensing[J]. Journal of Transportation Engineering, 1992, 118 (5): 700-710. doi: 10.1061/(ASCE)0733-947X(1992)118:5(700)
    [21] TANAKA N, UEMATSU K. A crack detection method in road surface images using morphology[C]//DBLP. Proceedings of IAPR Workshop on Machine Vision Applications. Trier: DBLP, 1998: 154-157.
    [22] 闫茂德, 伯绍波, 贺昱曜. 一种基于形态学的路面裂缝图像检测与分析方法[J]. 工程图学学报, 2008 (2): 142-147. doi: 10.3969/j.issn.1003-0158.2008.02.024

    YAN Mao-de, BO Shao-bo, HE Yu-yao. A method of image detection and analysis for pavement crack based on morphology[J]. Journal of Engineering Graphics, 2008 (2): 142-147. (in Chinese). doi: 10.3969/j.issn.1003-0158.2008.02.024
    [23] OLIVEIRA H, CORREIA P L. Automatic road crack segmentation using entropy and image dynamic thresholding[C]//IEEE. 17th European Signal Processing Conference. New York: IEEE, 2009: 622-626.
    [24] CHENG H D, CHEN Jim-rong, GLAZIER C, et al. Novel approach to pavement cracking detection based on fuzzy set theory[J]. Journal of Computing in Civil Engineering, 1999, 13 (4): 270-280. doi: 10.1061/(ASCE)0887-3801(1999)13:4(270)
    [25] CHENG H D, SHI X J, GLAZIER C. Real-time image thresholding based on sample space reduction and interpolation approach[J]. Journal of Computing in Civil Engineering, 2003, 17 (4): 264-272. doi: 10.1061/(ASCE)0887-3801(2003)17:4(264)
    [26] 李清泉, 刘向龙. 路面裂缝影像几何特征提取算法[J]. 中国科技论文在线, 2007, 2 (7): 517-522. https://www.cnki.com.cn/Article/CJFDTOTAL-ZKZX200707012.htm

    LI Qing-quan, LIU Xiang-long. An algorithm to image-based pavement cracks geometry features extraction[J]. Sciencepaper Online, 2007, 2 (7): 517-522. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-ZKZX200707012.htm
    [27] 孙波成, 邱延峻. 路面裂缝图像处理算法研究[J]. 公路交通科技, 2008, 25 (2): 64-68. doi: 10.3969/j.issn.1002-0268.2008.02.014

    SUN Bo-cheng, QIU Yan-jun. Pavement crack diseases recognition based on image processing algorithm[J]. Journal of Highway and Transportation Research and Development, 2008, 25 (2): 64-68. (in Chinese). doi: 10.3969/j.issn.1002-0268.2008.02.014
    [28] HUANG Ya-xiong, XU Bu-gao. Automatic inspection of pavement cracking distress[J]. Journal of Electronic Imaging, 2006, 15 (1), DOI: 10.1117/1.2177650.
    [29] SOMNCHAREAN S, PHIPHOBMONGKOL S. Crack detection on asphalt surface image using enhanced grid cell analysis[C]//IEEE. 4th IEEE International Symposium on Electronic Design, Test and Applications. New York: IEEE, 2008: 49-54.
    [30] 唐磊, 赵春霞, 王鸿南, 等. 基于图像三维地形模型的路面裂缝自动检测[J]. 计算机工程, 2008, 34 (5): 20-21, 38. https://www.cnki.com.cn/Article/CJFDTOTAL-JSJC200805009.htm

    TANG Lei, ZHAO Chun-xia, WANG Hong-nan, et al. Automated pavement crack detection based on image 3Dterrain model[J]. Computer Engineering, 2008, 34 (5): 20-21, 38. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-JSJC200805009.htm
    [31] 黄建平. 基于二维图像和深度信息的路面裂缝检测关键技术研究[D]. 哈尔滨: 哈尔滨工业大学, 2013.

    HUANG Jian-ping. Research on the key technologies of pavement crack inspection based on 2D image and depth information[D]. Harbin: Harbin Institute of Technology, 2013. (in Chinese).
    [32] 王刚, 贺安之, 肖亮. 基于高速公路裂纹局部线性特征内容的脊波变换域算法研究[J]. 光学学报, 2006, 26 (3): 341-346. doi: 10.3321/j.issn:0253-2239.2006.03.005

    WANG Gang, HE An-zhi, XIAO Liang. Algorithm research in ridgelet transform domain based on the image content of freeway local linear crack[J]. Acta Optica Sinica, 2006, 26 (3): 341-346. (in Chinese). doi: 10.3321/j.issn:0253-2239.2006.03.005
    [33] CHUA Koon-meng, XU Ling. Simple procedure for identifying pavement distresses from video images[J]. Journal of Transportation Engineering, 1994, 120 (3): 412-431. doi: 10.1061/(ASCE)0733-947X(1994)120:3(412)
    [34] LEE B J, LEE H D. Position-invariant neural network for digital pavement crack analysis[J]. Computer-Aided Civil and Infrastructure Engineering, 2004, 19 (2): 105-118. doi: 10.1111/j.1467-8667.2004.00341.x
    [35] 肖旺新, 严新平, 张雪. 基于混合密度因子的路面损坏自动识别研究[J]. 交通运输工程与信息学报, 2005, 3 (2): 19-26. doi: 10.3969/j.issn.1672-4747.2005.02.004

    XIAO Wang-xin, YAN Xin-ping, ZHANG Xue. Research on the automatic pavement distress recognition based on synthetical distress density factor[J]. Journal of Transportation Engineering and Information, 2005, 3 (2): 19-26. (in Chinese). doi: 10.3969/j.issn.1672-4747.2005.02.004
    [36] 丁爱玲, 焦李成. 基于支撑矢量机的路面损坏识别[J]. 长安大学学报: 自然科学版2007, 27 (2): 34-37.

    DING Ai-ling, JIAO Li-cheng. Automation of recogniting pavement surface distress based on support vector machine[J]. Journal of Chang'an University: Natural Science Edition, 2007, 27 (2): 34-37. (in Chinese).
    [37] OLIVEIRA H, CORREIA P L. Supervised strategies for cracks detection in images of road pavement flexible surfaces[C]//IEEE. 16th European Signal Processing Conference. New York: IEEE, 2008, 1-5.
    [38] 李清泉, 刘向龙. 路面影像破损加权评定方法[J]. 中国公路学报, 2009, 22 (4): 45-49. doi: 10.3321/j.issn:1001-7372.2009.04.008

    LI Qing-quan, LIU Xiang-long. Pavement image distress evaluation method based on weighted scheme[J]. China Journal of Highway and Transport, 2009, 22 (4): 45-49. (in Chinese). doi: 10.3321/j.issn:1001-7372.2009.04.008
    [39] TALAB A M A, HUANG Zhang-can, XI Fan, et al. Detection crack in image using Otsu method and multiple filtering in image processing techniques[J]. Optik-International Journal for Light and Electron Optics, 2016, 127 (3): 1030-1033. doi: 10.1016/j.ijleo.2015.09.147
    [40] ZOU Qin, CAO Yu, LI Qing-quan, et al. CrackTree: automatic crack detection from pavement images[J]. Pattern Recognition Letters, 2012, 33 (3): 227-238. doi: 10.1016/j.patrec.2011.11.004
    [41] SALMAN M, MATHAVAN S, KAMAL K, et al. Pavement crack detection using the Gabor filter[C]//IEEE. 16th International IEEE Annual Conference on Intelligent Transportation Systems. New York: IEEE, 2013: 2039-2044.
    [42] SONG Hong-xun, WANG Wei-xing, WANG Feng-ping, et al. Pavement crack detection by ridge detection on fractional calculus and dual-thresholds[J]. International Journal of Multimedia and Ubiquitous Engineering, 2015, 10 (4): 19-30. doi: 10.14257/ijmue.2015.10.4.03
    [43] 张德津, 李清泉, 陈颖, 等. 基于空间聚集特征的沥青路面裂缝检测方法[J]. 自动化学报, 2016, 42 (3): 443-454. https://www.cnki.com.cn/Article/CJFDTOTAL-MOTO201603010.htm

    ZHANG De-jin, LI Qing-quan, CHEN Ying, et al. Asphalt pavement crack detection based on spatial clustering feature[J]. Acta Automatica Sinica, 2016, 42 (3): 443-454. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-MOTO201603010.htm
    [44] RABAH M, EIHATTAB A, FAYAD A. Automatic concrete cracks detection and mapping of terrestrial laser scan data[J]. NRIAG Journal of Astronomy and Geophysics, 2013, 2 (2): 250-255. doi: 10.1016/j.nrjag.2013.12.002
    [45] CHOI J, ZHU L, KUROSU H. Detection of cracks in paved road surface using laser scan image data[C]//ISPRS. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vienna: ISPRS, 2016: 559-562.
    [46] LI Wei, HUYAN Ju, TIGHE S L, et al. Three-Dimensional pavement crack detection algorithm based on two-dimensional empirical mode decomposition[J]. Journal of Transportation Engineering Part B: Pavements, 2017, 143 (2), DOI: 10.1061/JPEODX.0000006.
    [47] ZHANG A, WANG K C P, LI Bao-xian, et al. Automated pixel-level pavement crack detection on 3Dasphalt surfaces using a deep-learning network[J]. Computer-aided Civil and Infrastructure Engineering, 2017, 32 (10): 805-819. doi: 10.1111/mice.12297
    [48] 宋宏勋, 马建, 王建锋, 等. 基于双相机立体摄影测量的路面裂缝识别方法[J]. 中国公路学报, 2015, 28 (10): 18-25, 40. doi: 10.3969/j.issn.1001-7372.2015.10.003

    SONG Hong-xun, MA Jian, WANG Jian-feng, et al. Identification of pavement crack based on dual camera stereo photogrammetry[J]. China Journal of Highway and Transport, 2015, 28 (10): 18-25, 40. (in Chinese). doi: 10.3969/j.issn.1001-7372.2015.10.003
    [49] 王建锋, 马建, 马荣贵, 等. 动位移的加速度精确测量技术研究[J]. 计算机科学, 2010, 37 (12): 201-202, 237. doi: 10.3969/j.issn.1002-137X.2010.12.046

    WANG Jian-feng, MA Jian, MA Rong-gui, et al. Study on calculation of dynamic displacement from time-frequency integration of acceleration[J]. Computer Science, 2010, 37 (12): 201-202, 237. (in Chinese). doi: 10.3969/j.issn.1002-137X.2010.12.046
    [50] 王建锋, 李平, 韩毅. 基于多传感器综合的路面不平度测量[J]. 武汉大学学报: 工学版, 2012, 45 (3): 361-365. https://www.cnki.com.cn/Article/CJFDTOTAL-WSDD201203018.htm

    WANG Jian-feng, LI Ping, HAN Yi. Road roughness measurement based on multi-sensor data comprehension[J]. Engineering Journal of Wuhan University, 2012, 45 (3): 361-365. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-WSDD201203018.htm
    [51] 吴秉军, 刘东海, 孙源泽, 等. 基于路面高程自动测量的全断面平整度计算方法[J]. 中国公路学报, 2016, 29 (11): 10-17. doi: 10.3969/j.issn.1001-7372.2016.11.002

    WU Bing-jun, LIU Dong-hai, SUN Yuan-ze, et al. Pavement roughness calculation of entire road surface based on automatic road elevation measuring[J]. China Journal of Highway and Transport, 2016, 29 (11): 10-17. (in Chinese). doi: 10.3969/j.issn.1001-7372.2016.11.002
    [52] 王建锋, 宋宏勋, 马荣贵. 基于阵列信号融合的路面平整度检测原理研究[J]. 微电子学与计算机, 2012, 29 (10): 69-73. https://www.cnki.com.cn/Article/CJFDTOTAL-WXYJ201210016.htm

    WANG Jian-feng, SONG Hong-xun, MA Rong-gui. Road roughness detection method based on array signals processing[J]. Microelectronics and Computer, 2012, 29 (10): 69-73. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-WXYJ201210016.htm
    [53] DU Yu-chuan, LIU Cheng-long, WU Di-fei, et al. Application of vehicle mounted accelerometers to measure pavement roughness[J]. International Journal of Distributed Sensor Networks, 2016, DOI: 10.1155/2016/8413146.
    [54] 毛庆洲, 叶浩, 丁诗雄, 等. 基于小波变换的路面平整度自适应提取算法[J]. 中国公路学报, 2015, 28 (10): 11-17. doi: 10.3969/j.issn.1001-7372.2015.10.002

    MAO Qing-zhou, YE Hao, DING Shi-xiong, et al. Adaptive extraction algorithm of pavement roughness based on wavelet transformation[J]. China Journal of Highway and Transport, 2015, 28 (10): 11-17. (in Chinese). doi: 10.3969/j.issn.1001-7372.2015.10.002
    [55] 王建锋, 宋宏勋, 马荣贵. 路面平整度评价指标IRI的影响因素[J]. 重庆交通大学学报: 自然科学版, 2012, 31 (6): 1145-1148. https://www.cnki.com.cn/Article/CJFDTOTAL-CQJT201206013.htm

    WANG Jian-feng, SONG Hong-xun, MA Rong-gui. Influencing factors of international roughness index[J]. Journal of Chongqing Jiaotong University: Natural Science, 2012, 31 (6): 1145-1148. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-CQJT201206013.htm
    [56] DU Yu-chuan, LIU Cheng-long, WU Di-fei, et al. Measurement of international roughness index by using Z-axis accelerometers and GPS[J]. Mathematical Problems in Engineering, 2014, DOI: 10.1155/2014/928980.
    [57] 江东, 刘绪坤. 基于磁悬浮振动测试技术的公路平整度测试研究[J]. 仪表技术与传感器, 2017 (2): 102-106. doi: 10.3969/j.issn.1002-1841.2017.02.026

    JIANG Dong, LIU Xu-kun. Road flatness detection based on magnetic levitation vibration measurement technique[J]. Instrument Technique and Sensor, 2017 (2): 102-106. (in Chinese). doi: 10.3969/j.issn.1002-1841.2017.02.026
    [58] 刘庆华, 周帏, 何仁, 等. 基于优化模糊C均值聚类算法的路面不平度识别[J]. 农业工程学报, 2014, 30 (22): 195-200. doi: 10.3969/j.issn.1002-6819.2014.22.024

    LIU Qing-hua, ZHOU Wei, HE Ren, et al. Road roughness recognition based on improved fuzzy C-mean algorithm combined with genetic algorithm[J]. Transactions of the Chinese Society of Agricultural Engineering, 2014, 30 (22): 195-200. (in Chinese). doi: 10.3969/j.issn.1002-6819.2014.22.024
    [59] 崔丹丹, 张才千, 韩东. 基于BP神经网络的路面不平度检测与仿真[J]. 计算机仿真, 2014, 31 (5): 162-166. doi: 10.3969/j.issn.1006-9348.2014.05.036

    CUI Dan-dan, ZHANG Cai-qian, HAN Dong. Road roughness detection and simulation based on BP neural network[J]. Computer Simulation, 2014, 31 (5): 162-166. (in Chinese). doi: 10.3969/j.issn.1006-9348.2014.05.036
    [60] WANG Wei, BEI Shao-yi, ZHANG Lan-chun, et al. Pavement roughness identification research in time domain based on neural network[J]. Journal of Vibroengineering, 2015, 17 (7): 3865-3875.
    [61] 王建锋, 马建, 马荣贵, 等. 精确车辙检测系统的研究与开发[J]. 微电子学与计算机, 2011, 28 (2): 175-177, 180. https://www.cnki.com.cn/Article/CJFDTOTAL-WXYJ201102041.htm

    WANG Jian-feng, MA Jian, MA Rong-gui, et al. Research and development of detection system for road rut[J]. Microelectronics and Computer, 2011, 28 (2): 175-177, 180. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-WXYJ201102041.htm
    [62] 李莉, 孙立军, 谭生光, 等. 用于路面车辙检测的线结构光图像处理流程[J]. 同济大学学报: 自然科学版, 2013, 41 (5): 710-715. doi: 10.3969/j.issn.0253-374x.2013.05.013

    LI Li, SUN Li-jun, TAN Sheng-guang, et al. Line-structured light image processing procedure for pavement rut detection[J]. Journal of Tongji University: Natural Science, 2013, 41 (5): 710-715. (in Chinese). doi: 10.3969/j.issn.0253-374x.2013.05.013
    [63] WANG C Y, TAN Q C, GUO R H. Design and optimization of a linear laser beam[J]. Lasers in Engineering, 2014, 27 (5/6): 373-381.
    [64] WEI Yun-tao, HONG Han-yu, ZHANG Xiu-hua, et al. Anew method for automatic detection of rut feature based on road laser images[C]//SPIE. 6th International Symposium on Multispectral Image Processing and Pattern Recognition. Breda: SPIE, 2009, DOI: 10.1117/12.833155.
    [65] 陈小宇, 雷波. 一种快速鲁棒的车辙检测方法[J]. 应用科学学报, 2013, 31 (5): 512-518. doi: 10.3969/j.issn.0255-8297.2013.05.011

    CHEN Xiao-yu, LEI Bo. Fast and robust measurement of pavement ruts[J]. Journal of Applied Sciences, 2013, 31 (5): 512-518. (in Chinese). doi: 10.3969/j.issn.0255-8297.2013.05.011
    [66] 李清泉, 雷波, 毛庆洲, 等. 利用激光三角法进行快速车辙检测[J]. 武汉大学学报: 信息科学版, 2010, 35 (3): 302-307. https://www.cnki.com.cn/Article/CJFDTOTAL-WHCH201003015.htm

    LI Qing-quan, LEI Bo, MAO Qing-zhou, et al. A fast method for pavement ruts measuring with laser triangulation[J]. Geomatics and Information Science of Wuhan University, 2010, 35 (3): 302-307. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-WHCH201003015.htm
    [67] KAGE T, MATSUSHIMA K. Method of rut detection using lasers and in-vehicle stereo camera[C]//IEEE. 2015International Conference on Intelligent Informatics and Biomedical Sciences. New York: IEEE, 2015: 48-53.
    [68] ZHANG Yue, GAO Ting-ting. VC-based rutting digital imaging automatic detection technology research and design for road construction[J]. Advanced Materials Research, 2012 (461): 370-372.
    [69] CUI Xin-zhuang, ZHOU Xing-lin, LOU Jun-jie, et al. Measurement method of asphalt pavement mean texture depth based on multi-line laser and binocular vision[J]. International Journal of Pavement Engineering, 2017, 18 (5): 459-471. doi: 10.1080/10298436.2015.1095898
    [70] 刘仪培, 皇甫皝. 路表构造特征的沥青路面抗滑性能评价方法研究[J]. 黑龙江交通科技, 2016 (3): 1-3. https://www.cnki.com.cn/Article/CJFDTOTAL-HLJJ201603001.htm

    LIU Yi-pei, HUANG Pu-guang. Study on asphalt pavement skid resistance evaluation method based on the road surface structural features[J]. Communications Science and Technology Heilongjiang, 2016 (3): 1-3. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-HLJJ201603001.htm
    [71] 马荣贵, 王建锋, 李平. 沥青路面构造深度精确检测方法研究[J]. 科学技术与工程, 2014, 14 (8): 265-268. doi: 10.3969/j.issn.1671-1815.2014.08.052

    MA Rong-gui, WANG Jian-feng, LI Ping. Research on high precision measurement of pavement texture depth[J]. Science Technology and Engineering, 2014, 14 (8): 265-268. (in Chinese). doi: 10.3969/j.issn.1671-1815.2014.08.052
    [72] 刘琬辰, 黄晓明. 基于图像处理的沥青路面构造深度评价方法的优化研究[J]. 北方交通, 2013 (3): 9-13. doi: 10.3969/j.issn.1673-6052.2013.03.004

    LIU Wan-chen, HUANG Xiao-ming. Optimization research of the asphalt pavement surface texture evaluation based on digital image[J]. Northern Communications, 2013 (3): 9-13. (in Chinese). doi: 10.3969/j.issn.1673-6052.2013.03.004
    [73] 王景彬. 高速公路沥青路面检测方法及注意事项探究[J]. 建筑知识, 2017 (10): 153-154.

    WANG Jing-bin. Study on detection methods and precautions of asphalt pavement of expressway[J]. Architectural Knowledge, 2017 (10): 153-154. (in Chinese).
    [74] 宁斌权. 基于数字图像技术的沥青路面构造深度的评价方法[J]. 装备技术, 2017 (7): 143, 65. https://www.cnki.com.cn/Article/CJFDTOTAL-HEFE201710017.htm

    NING Bin-quan. The evaluation method of asphalt pavement construction depth based on digital image technology[J]. Equipment Technology, 2017 (7): 143, 65. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-HEFE201710017.htm
    [75] CIGADA A, MANCOSU F, MANZONI S, et al. Lasertriangulation device for in-line measurement of road texture at medium and high speed[J]. Mechanical Systems and Signal Processing, 2010, 24 (7): 2225-2234. doi: 10.1016/j.ymssp.2010.05.002
    [76] 周兴林, 蒋难得, 肖旺新, 等. 基于激光视觉的沥青路面构造深度测量方法[J]. 中国公路学报, 2014, 27 (3): 11-16. https://www.cnki.com.cn/Article/CJFDTOTAL-ZGGL201403003.htm

    ZHOU Xing-lin, JIANG Nan-de, XIAO Wang-xin, et al. Measurement method for mean texture depth of asphalt pavement based on laser vision[J]. China Journal of Highway and Transport, 2014, 27 (3): 11-16. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-ZGGL201403003.htm
    [77] 王旭东. 沥青路面弯沉指标的探讨[J]. 公路交通科技, 2015, 32 (1): 1-12, 24. doi: 10.3969/j.issn.1002-0268.2015.01.001

    WANG Xu-dong. Discussion of asphalt pavement deflection indicator[J]. Journal of Highway and Transportation Research and Development, 2015, 32 (1): 1-12, 24. (in Chinese). doi: 10.3969/j.issn.1002-0268.2015.01.001
    [78] 胡蓉. 杭州市政道路动态弯沉检测及半刚性路面结构适用性分析[D]. 杭州: 浙江大学, 2014.

    HU Rong. Research on dynamic deflection testing and semirigid pavement structure applicability of Hangzhou municipal roads[D]. Hangzhou: Zhejiang University, 2014. (in Chinese).
    [79] 吴玉, 蒋鑫, 梁雪娇, 等. 轮载作用下典型沥青路面结构力学行为分析[J]. 西南交通大学学报, 2017, 52 (3): 563-570. doi: 10.3969/j.issn.0258-2724.2017.03.017

    WU Yu, JIANG Xin, LIANG Xue-jiao. Mechanical behaviors of typical asphalt pavement structures under wheel loads[J]. Journal of Southwest Jiaotong University, 2017, 52 (3): 563-570. (in Chinese). doi: 10.3969/j.issn.0258-2724.2017.03.017
    [80] 李盛, 陈尚武, 刘朝晖, 等. 旧水泥混凝土路面弯沉测试的若干问题研究[J]. 中南大学学报: 自然科学版, 2015, 46 (12): 4713-4718. doi: 10.11817/j.issn.1672-7207.2015.12.044

    LI Sheng, CHEN Shang-wu, LIU Chao-hui, et al. Some problems on deflection test of old cement concrete pavement[J]. Journal of Central South University: Science and Technology, 2015, 46 (12): 4713-4718. (in Chinese). doi: 10.11817/j.issn.1672-7207.2015.12.044
    [81] 周岚, 倪富键, 王浩仰. 基于弯沉盆的高速公路沥青混凝土路面结构状况评价研究[J]. 公路, 2015 (9): 1-6. https://www.cnki.com.cn/Article/CJFDTOTAL-GLGL201509001.htm

    ZHOU Lan, NI Fu-jian, WANG Hao-yang. Research on evaluation of highway asphalt pavement structure based on deflection basin[J]. Highway, 2015 (9): 1-6. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-GLGL201509001.htm
    [82] 赵永胜. G207锡海线公路改建工程路基弯沉检测方法对比分析[J]. 黑龙江交通科技, 2016 (9): 24-25. doi: 10.3969/j.issn.1008-3383.2016.09.013

    ZHAO Yong-sheng. Contrastive analysis of subgrade detection methods for Highway G207Xihai Line reconstruction project[J]. Communications Science and Technology Heilongjiang, 2016 (9): 24-25. (in Chinese). doi: 10.3969/j.issn.1008-3383.2016.09.013
    [83] 洪亮, 杨帆, 付丽, 等. 前插式激光测距自动弯沉仪校准及贝克曼梁对比试验分析[J]. 交通标准化, 2014, 42 (17): 149-153, 156. https://www.cnki.com.cn/Article/CJFDTOTAL-JTBH201417038.htm

    HONG Liang, YANG Fan, FU Li, et al. Contrast test analysis on front-insert type auto deflectometer with laser range meter and Benkelman beam method[J]. Transportation Standardization, 2014, 42 (17): 149-153, 156. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-JTBH201417038.htm
    [84] GEORGE V, KUMAR A. Studies on modulus of resilience using cyclic tri-axial test and correlations to PFWD, DCP and CBR[J]. International Journal of Pavement Engineering, 2016: 1-10.
    [85] CHAI G, MANOHARAN S, GOLDING A, et al. Evaluation of the traffic speed deflectometer data using simplified deflection model[J]. Transportation Research Procedia, 2016, 14: 3031-3039. doi: 10.1016/j.trpro.2016.05.444
    [86] 郑佳麒. GPR信号处理技术研究及在道路沥青注浆评价中的应用[J]. 交通科技, 2017 (2): 143-146. https://www.cnki.com.cn/Article/CJFDTOTAL-SKQB201702044.htm

    ZHENG Jia-qi. Research on GPR data processing and application on the evaluation of asphalt grouting[J]. Transportation Science and Technology, 2017 (2): 143-146. (in Chinese). https://www.cnki.com.cn/Article/CJFDTOTAL-SKQB201702044.htm
    [87] AHMED M, TAREFDER R, MAJI A, et al. Variation of FWD modulus due to incorporation of GPR predicted layer thicknesses[C]//IEEE. 15th International Conference on Ground Penetrating Radar. New York: IEEE, 2014: 345-350.
    [88] MARECOS V, FONTUL S, DE LURDES ANTUNES M. Evaluation of a highway pavement using non-destructive tests: falling weight deflectometer and ground penetrating radar[J]. Construction and Building Materials, 2017, 154: 1164-1172. doi: 10.1016/j.conbuildmat.2017.07.034
    [89] AHMED M U, TAREFDER R A. Incorporation of GPR and FWD into pavement mechanistic-empirical design[J]. Construction and Building Materials, 2017, 154: 1272-1282. doi: 10.1016/j.conbuildmat.2017.06.105
  • 加载中
计量
  • 文章访问数:  4528
  • HTML全文浏览量:  3477
  • PDF下载量:  2228
  • 被引次数: 0
出版历程
  • 收稿日期:  2017-11-02
  • 刊出日期:  2017-10-25

目录

    /

    返回文章
    返回