A real-time monitoring system for lift-thickness control in highway construction

被引:29
作者
Liu, Donghai [1 ]
Wu, You [1 ]
Li, Shuai [2 ]
Sun, Yuanze [1 ]
机构
[1] Tianjin Univ, State Key Lab Hydraul Engn Simulat & Safety, 92 Weijin Rd, Tianjin 300072, Peoples R China
[2] Purdue Univ, Lyles Sch Civil Engn, 550 Stadium Mall Dr, W Lafayette, IN 47907 USA
基金
中国国家自然科学基金;
关键词
Highway construction; Lift-thickness; Quality control; Real-time monitoring; Robotic total station (RTS); Laser; MODEL; GPR;
D O I
10.1016/j.autcon.2015.12.004
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Monitoring and controlling lift-thickness are critical in pavement construction, because lift-thickness can affect the durability and long-term performance of pavement. Existing methods for measuring lift-thickness are not sufficient due to four limitations. First, the reliability of manual measurements is questionable, since manual measurements can only be conducted at sparse points instead of entire pavement surface. Second, the accuracy of lift-thickness measurement is not satisfactory. For instance, the string-line method and balance beam system are unable to achieve millimeter-level accuracy. Third, current techniques cannot indicate the accurate positions of weak areas where the lift-thickness is not compliant with construction standards. Fourth, the agency and supervisor cannot monitor lift-thickness remotely in real time with current techniques. To overcome the above limitations, this study created a novel system that integrates inclinometer, robotic total station, laser ranging sensors, and wireless communication technologies to monitor lift-thickness during highway construction. The elevations of datum plane and the layer being paved can be accurately obtained using this system. Lift thickness then is measured in real-time as the difference between the elevations. Visualization of weak areas, warning messages, and monitoring reports are synchronized among the operator, contractor, supervisor and agency, guiding them to adjust operations and to ensure paving quality. Field applications demonstrated that this newly created system could monitor lift-thickness in an automatic, accurate, continuous, and real-time manner. In addition, the operator, contractor, supervisor and agency could access the information of construction quality simultaneously; and thus work closely to resolve quality issues in time. This system facilitates an integrated quality control mode that is suitable for the construction industry. (C) 2015 Elsevier B.V. All rights reserved.
引用
收藏
页码:27 / 36
页数:10
相关论文
共 50 条
[41]   A framework for real-time monitoring and early warning to scaffold safety at construction site [J].
Xue, Xiaolong ;
Shi, Ning ;
Chen, Xiang ;
Wang, Chengwu ;
Zhao, Qi ;
Luo, Yazhuo .
Journal of Convergence Information Technology, 2012, 7 (19) :140-146
[42]   Application of real-time monitoring technology to foundation settlement of sloping breakwaters in construction [J].
Wang W. ;
Xu K. ;
Wang H.-L. ;
Li L.-L. .
Yantu Gongcheng Xuebao/Chinese Journal of Geotechnical Engineering, 2017, 39 :85-90
[43]   Study on real-time construction quality monitoring of storehouse surfaces for RCC dams [J].
Liu, Yuxi ;
Zhong, Denghua ;
Cui, Bo ;
Zhong, Guiliang ;
Wei, Yongxin .
AUTOMATION IN CONSTRUCTION, 2015, 49 :100-112
[44]   GNSS System Time Offset Real-Time Monitoring with GLONASS ICBs Estimated [J].
Kong, Sijia ;
Peng, Jing ;
Liu, Wenxiang ;
Wang, Mengli ;
Wang, Feixue .
2018 IEEE 3RD INTERNATIONAL CONFERENCE ON IMAGE, VISION AND COMPUTING (ICIVC), 2018, :837-840
[45]   A real-time monitoring approach for bivariate event data [J].
Zwetsloot, Inez Maria ;
Mahmood, Tahir ;
Taiwo, Funmilola Mary ;
Wang, Zezhong .
APPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY, 2023, 39 (06) :789-817
[46]   Microgrids' Control Strategies and Real-Time Monitoring Systems: A Comprehensive Review [J].
Ojo, Kayode Ebenezer ;
Saha, Akshay Kumar ;
Srivastava, Viranjay Mohan .
ENERGIES, 2025, 18 (13)
[47]   Automatic control and real-time monitoring system for earth-rock dam material truck watering [J].
Liu, Donghai ;
Cui, Bo ;
Liu, Yugang ;
Zhong, Denghua .
AUTOMATION IN CONSTRUCTION, 2013, 30 :70-80
[48]   Real-time quality monitoring and control system using an integrated cost effective support vector machine [J].
YeongGwang Oh ;
Moise Busogi ;
Kasin Ransikarbum ;
Dongmin Shin ;
Daeil Kwon ;
Namhun Kim .
Journal of Mechanical Science and Technology, 2019, 33 :6009-6020
[49]   Real-time monitoring and optimization of machine learning intelligent control system in power data modeling technology [J].
Wang, Qiong ;
Chen, Zuohu ;
Zhou, Yongbo ;
Liu, Zhiyuan ;
Peng, Zhenguo .
MACHINE LEARNING WITH APPLICATIONS, 2024, 18
[50]   Monitoring and control framework for intelligent real-time optimization of printing sequence of powder bed fusion [J].
Malekipour, Ehsan ;
El-Mounayri, Hazim ;
Hagedorn-Hansen, Devon .
JOURNAL OF INTELLIGENT MANUFACTURING, 2025, 36 (01) :375-398