摘要
为了研究沥青面层压实程度与压实均匀性的评价方法,提高沥青面层压实质量,利用探地雷达系统对沥青面层压实参数进行检测,并连续输出大样本测量数据.根据规范中压实度要求并提出压实薄弱区间作为沥青面层压实程度评价指标,采用变异系数作为沥青层压实度数值分布均匀性的评价指标,引进半变异函数中的偏基台值为压实度空间变异程度的评价指标.采用上述指标对某市政路SMA-13沥青上面层压实质量进行评价,结果表明:采用探地雷达检测技术,可以快速、无损地对沥青面层压实质量进行评价,并可反映施工过程中存在的问题,为改进与提升施工工艺提供了理论依据与指导.
In order to study the evaluation method of compaction degree and compaction uniformity of asphalt layer and improve its compaction quality,the Ground Penetrating Radar(GPR)test system was used to collect the compaction parameter of asphalt layer and output continuous large samples.In this paper,the requirement of compactness in the specification and the weak compaction zone were proposed as the evaluation index of compaction degree of asphalt layer.The variation coefficient and the partial abutment value in the semi variation function were used as the evaluation indexes of the numerical distribution uniformity and spatial variation degree of the compactness,respectively.The above proposed indexes were utilized to evaluate the compaction quality of SMA-13 surface layer of a municipal road.The results show that the GPR detection technology can evaluate the compaction quality of asphalt layer quickly and non destructively,and reflect the faults in the construction process,which can provide rationale and guidance for improving and upgrading the construction technology.
作者
凌天清
刁航
田波
崔立龙
彭博
LING TianQing;DIAO Hang;TIAN Bo;CUI LiLong;PENG Bo(Key Laboratory of Transport Industry of Road Structure and Material,Research Institute of Highway,Ministry of Transport,Beijing 100088,China;School of Civil Engineering,Chongqing Jiaotong University,Chongqing 400074,China;School of Transportation and Vehicle Engineering,Shandong University of Technology,Shandong,Zibo 255000,China;School of Materials Science and Engineering,Chongqing Jiaotong University,Chongqing 400074,China)
出处
《地球物理学进展》
CSCD
北大核心
2023年第6期2724-2733,共10页
Progress in Geophysics
基金
道路结构与材料交通运输行业重点实验室(交通运输部公路科学研究所)2019年度开放基金(S282019124)
重庆市技术创新与应用发展专项面上项目(cstc2019jscx-msxmX0296)联合资助。
关键词
道路工程
沥青面层
探地雷达
压实质量
Deep learning
Ground Penetrating Radar(GPR)
Railway subgrade disease detection
Sleeper noise suppression