摘要
针对高速弯沉仪检测数据的规律和特点,提出了基于支持向量机模型的水泥道面板底脱空检测方法。介绍了高速激光弯沉仪的系统组成及测量原理;对高速弯沉仪和重型落锤式弯沉仪进行了对比试验研究,分析了基于弯沉比的脱空判定方法对高速弯沉仪检测结果的适用性,基于支持向量机模型建立了道面板底脱空程度分类识别模型。结果表明:高速弯沉仪与重型落锤式弯沉仪对道面薄弱区段的识别结果显示较高的一致性;所建立的支持向量机脱空程度分类模型具有较好的综合性能,二分类和三分类均有较高的预测精度。
According to the rules and characteristics of the test data of traffic speed deflectometer(TSD),a method based on support vector machine(SVM)model was proposed to detect the void at the bottom of cement pavement slab.The system composition and measuring principle of TSD was introduced.The contrast test of TSD and heavy weight deflectometer(HWD)was carried out.The applicability of the void determination method based on deflection ratio to the detection results of TSD was analyzed,and the classification recognition model of the void degree at the bottom of the pavement slab was established based on the SVM model.The results show that:the identification results of weak sections of the pavement by TSD and HWD show high consistency;the constructed SVM void degree classification model has good comprehensive performance,and both two and three classification have high prediction accuracy.
作者
李忠玉
冯汉卿
丛林
陈永辉
LI Zhongyu;FENG Hanqing;CONG Lin;CHEN Yonghui(Henan Key Laboratory of High Grade Highway Detection and Maintenance Technology,Xinxiang,Henan 453003,China;Key Laboratory of Road and Traffic Engineering of the Ministry of Education,Tongji University,Shanghai 201804,China)
出处
《重庆交通大学学报（自然科学版）》
CAS
CSCD
北大核心
2023年第1期66-73,90,共9页
Journal of Chongqing Jiaotong University(Natural Science)
基金
国家重点研发计划政府间国际科技创新合作重点专项项目(2016YFE0111000)
民航机场安全与运行工程技术研究中心开放课题(KFKT2021-07)
上海市交通委2021年度科研计划项目(JT2021-KY-014)。
关键词
道路与机场工程
水泥道面
脱空检测
高速激光弯沉仪
支持向量机
道路检测
road and airport engineering
concrete pavement
void detection
traffic speed deflectometer(TSD)
support vector machine(SVM)
road detection
作者简介
第一作者:李忠玉(1968—),男,河南新乡人,高级工程师,主要从事道路检测技术方面的研究。E-mail:439472056@qq.com;通信作者:丛林(1974—),男,山东威海人,教授,博士,主要从事路基路面工程方面的研究。E-mail:conglin@tongji.edu.cn。
