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作 者:曾晟[1] 梁乃兴[1] 薛轲 杜镇宇 ZENG Sheng;LIANG Naixing;XUE Ke;DU Zhenyu(School of Civil Engineering,Chongqing Jiaotong University,Chongqing 400074,China;College of Transportation Engineering,Tongji University,Shanghai 200092,China)
机构地区:[1]重庆交通大学土木工程学院,重庆400074 [2]同济大学交通运输学院,上海200092
出 处:《哈尔滨工业大学学报》2019年第9期144-148,共5页Journal of Harbin Institute of Technology
基 金:云南省交通运输厅科技项目(2017(A)015);重庆市研究生科研创新项目(2017B0106);重庆市教委科学技术研究项目(KJQN201800704)
摘 要:为了在沥青路面摊铺阶段对混合料均匀性进行实时评价,实时反馈、指导施工,减少离析现象,运用数字图像处理技术,通过对摊铺沥青混合料图像进行灰度化、滤波、图像二值化等图像预处理,并通过图像集料颗粒面积比验证预处理准确性;以图像中9.5 mm以上颗粒静矩标准差评价摊铺沥青混合料数字图像均匀性,通过计算施工现场采集的1 085张摊铺沥青混合料图像静矩标准差进行试验验证并提出数字图像摊铺沥青混合料均匀性评价指标.结果表明:数字图像处理技术预处理得到的图像中颗粒面积比值与按实际混合料配合比计算的面积比基本相符;通过min-max标准化后静矩标准差的值与对应图像进行对比分析,提出了均匀性评价指标,为摊铺沥青混合料离析检测提供一种新方法.The accurate and timely monitoring of asphalt mixture paving process is critical for reducing segregation and effective construction. In this study, 1085 construction site images were pre-processed by digital image processing techniques(i.e., grayscale, filtration, and binarization) to explore and build up a real-time evaluation method for paving asphalt mixture during construction process. The sum and standard deviation of the static moment of each particle larger than 9.5 mm was calculated and the min-max normalized standard deviation were utilized to evaluate the paving asphalt mixture distribution uniformity. Results show that the mix proportion value from the proposed image technique was close to the value from the reality. By comparing the value of min-max normalized static moment standard deviation with the corresponding image, a uniformity indicator was proposed for the evaluation of asphalt pavement uniformity during paving process. The paper provides a new method for paving asphalt mixture segregation detection.
关 键 词:沥青混合料 摊铺均匀性 图像处理技术 图像预处理 静矩理论
分 类 号:U416.217[交通运输工程—道路与铁道工程]
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