Design and implementation of SHM system for highway tunnels

doi:10.16265/j.cnki.issn1003-3033.2022.07.1444

Abstract

Abstract:

In order to reduce structural damages of mountain highway tunnels during operation, to improve operation management and reduce maintenance costs, a structural health monitoring system for the tunnel was developed by utilizing SHM and automatic monitoring technology. Then, overall system framework, core subsystems and various functions were established by adopting C series programming language, C/S structure and 4-layer architecture system. Finally, experiments were conducted in Chang'an tunnel of Huaiyang expressway to verify applicability and effectiveness of the system. The results show that the proposed system can collect, organize and store monitoring data of various types of sensors in real time, analyze and process data (such as curve analysis, over-limit monitoring and early warning and forecasting, etc.), correlate measurement points with CAD drawings, and comprehensively evaluate tunnel structural health and generate reports automatically.

Key words: mountain highway tunnel, structural health monitoring (SHM), automated monitoring, analytical processing, comprehensive evaluation

XIE Quanmin, MA Wei, YANG Wendong. Design and implementation of SHM system for highway tunnels[J]. China Safety Science Journal, 2022, 32(7): 56-62.

Figures/Tables 8

Fig.1

Fig.2

Fig.3

Fig.4

Fig.5

Fig.6

Tab.1

Tab.2

References 14

[1]	张顶立. 隧道及地下工程的基本问题及其研究进展[J]. 力学学报, 2017, 49(1):3-21. doi: 10.6052/0459-1879-16-348
	ZHANG Dingli. Essential issues and their research progress in tunnel and underground engineering[J]. Chinese Journal of Theoretical and Applied Mechani, 2017, 49(1): 3-21.
[2]	中华人民共和国交通运输部. 2020年交通运输行业发展统计公报[J]. 交通财会, 2021(6):92-96.
[3]	马桂苗. 公路隧道设计安全风险评估[J]. 中国公路, 2012(18):116 -117.
[4]	HE Chuan, WANG Bo. Research progress and development trends of highway tunnels in China[J]. Journal of Modern Transportation, 2013, 21(4):209-223. doi: 10.1007/s40534-013-0029-4
[5]	LIU Qi, LU Guangyin, HUANG Junrong, et al. Development of tunnel intelligent monitoring and early warning system based on micro-service architecture: the case of Anping tunnel[J]. Geomatics, Natural Hazards and Risk, 2020, 11(1):1404-1425. doi: 10.1080/19475705.2020.1797906
[6]	吴贤国, 王雷, 陈虹宇, 等. 基于BIM技术的物联网运营地铁结构健康监测系统设计与实现[J]. 隧道建设, 2020, 40(6):905-914.
	WU Xianguo, WANG Lei, CHEN Hongyu, et al. Design and realization of health monitoring system for operation metro structure based on BIM-based internet of things[J]. Tunnel Construction, 2020, 40(6):905-914.
[7]	喻钢, 史礼华. 基于MR与微服务的隧道应急模拟与推演系统[J]. 中国安全科学学报, 2020, 30(1):162-167. doi: 10.16265/j.cnki.issn1003-3033.2020.01.025
	YU Gang, SHI Lihua. Tunnel emergency simulation and deduction system based on MR and microservice[J]. China Safety Science Journal, 2020, 30(1): 162-167. doi: 10.16265/j.cnki.issn1003-3033.2020.01.025
[8]	陈卫忠, 李长俊, 曾灿军, 等. 大型水下盾构隧道结构健康监测系统的构建与应用[J]. 岩石力学与工程学报, 2018, 37(1):1-13.
	CHEN Weizhong, LI Changjun, ZENG Canjun, et al. Establishment and application of structural health monitoring system for large shield tunnel[J]. Chinese Journal of Rock Mechanics and Engineering, 2018, 37(1): 1-13.
[9]	杨超斌, 赵荣欣, 吴华勇. 钱江隧道结构健康监测系统的设计与应用[J]. 上海公路, 2017(2):41-44.
	YANG Chaobin, ZHAO Rongxin, WU Huayong. Design and application of Qianjiang tunnel structural health monitoring system[J]. Shanghai Highway, 2017(2): 41-44.
[10]	GIULIA B, LUCA S, GIANLUCA M. Structural health monitoring of a road tunnel intersecting a large and active landslide[J]. Applied Sciences-Basel, 2017, 7(12): DOI: 10.3390/app7121271. doi: 10.3390/app7121271
[11]	ALDO M, ESTER C, AGNESE C, et al. Distributed fiber optic sensors for the monitoring of a tunnel crossing a landslide[J]. Remote Sensing, 2018, 10(8):DOI: 10.33901rs1008129. doi: 10.33901rs1008129
[12]	刘毅, 李海枫, 商峰. 双层复合衬砌隧洞运行安全预警监控指标研究[J]. 中国水利水电科学研究院学报, 2021, 19(1):74-80.
	LIU Yi, LI Haifeng, SHANG Feng. Research on operation safety warning and monitoring index of double layer composite lining tunnel[J]. Journal of China Institute of Water Resources and Hydropower Research, 2021, 19(1): 74-80.
[13]	王洪德, 高秀鑫. 高速公路隧道健康诊断及预警的模糊神经网络方法[J]. 中国安全科学学报, 2014, 24(2): 9-15.
	WANG Hongde, GAO Xiuxin. Method of fuzzy neural network for expressway tunnel health diagnosis and early-warning[J]. China Safety Science Journal, 2014, 24(2): 9-15.
[14]	JTG/T 3660—2020,公路隧道施工技术规范[S].
	JTG/T 3660-2020, Technical specifications for construction of highway tunnel[S].

监测项目	采集设备	型号	精度	数量
混凝土应变	混凝土应变计	EM-5	±0.5/100	40支
钢筋应力	钢筋应力计	IRHP	±1.0/100	40支
断面收敛	收敛监测仪	CD70A	0.1mm	4套
远程监测单元	数据采集仪	DT85G	—	2套
远程监测单元	扩展模块	CEM20	—	4套

序号	安全等级评价指标	A	B	C	D	E
序号	安全等级评价指标	完好	轻微	较严重	严重	极严重
1	钢筋应力 σ/MPa	<188	188≤σ<215	215≤σ<240	240≤σ<268	≥268
2	混凝土应变 ε/10^-6	<372(压) <33(拉)	372≤ε<426 (压) 33≤ε<38(拉)	426≤ε<479 (压) 38≤ε<43(拉)	479≤ε<532 (压) 43≤ε<48(拉)	≥532 (压) ≥48(拉)
3	断面收敛 v /(mm·d^-1)	<0.15	0.15≤v<0.4	0.4≤v<0.5	0.6≤v<0.7	≥0.7
4	衬砌漏水	0	1(拱部有季节性滴水、边墙有季节性淌水)	2(拱部有滴水、边墙有淌水)	3(拱部滴水星线、边墙淌水流泥)	4(拱部漏水直击接触网,影响正常运营)
5	衬砌裂纹	0	1(有收缩或环向裂纹)	2(裂纹多于3条、有交叉:裂纹长<5 m、宽度<3 mm)	3(网状裂纹、有剥落掉块可能;裂纹长5~10 m,宽3~5 mm)	4(裂纹呈网状、有剥落掉快;裂纹长>10 m、宽>5 mm)
健康等级描述		完好状态。无异常情况。	轻微破损。存在轻微破损,现阶段趋于稳定,对交通安全不会有影响	中等破损。存在破坏,发展缓慢,可能会影响交通安全	严重破损。存在较严重破坏,发展较快,已影响交通安全	危险状态。存在严重破坏,发展迅速,已危及交通安全
养护对策		正常养护	检查结构破损部位,必要时实施保养维修	重点监测结构破损部位,实施保养维修	尽快治理结构破损部位,实施交通管制	及时关闭隧道,及时全面地治理破坏部位

[1]	ZHU Anfeng, FAN Xiufang, DU Wenrui, SUN Wanxin, XU Gang. Comprehensive evaluation of disaster prevention and mitigation capacity of emergency shelters based on resilience perspective: a case study of Ouhai district in Wenzhou [J]. China Safety Science Journal, 2024, 34(5): 223-230.
[2]	CHEN Liang, ZHENG Wei. Research on causes of dispatcher fatigue based on AWAHP [J]. China Safety Science Journal, 2024, 34(4): 42-49.
[3]	HUANG Guoping, LEI Haoxiang. Comprehensive evaluation of emergency logistics suppliers based on cloud TOPSIS method [J]. China Safety Science Journal, 2024, 34(2): 217-224.
[4]	ZHOU Haiyi, BAO Quangui, YE Mao, ZHU Shengwen, LIN Yingdian. Fuzzy comprehensive evaluation of urban bridge reliability based on combination weighting method [J]. China Safety Science Journal, 2023, 33(S1): 156-161.
[5]	CHEN Na, GUO Haoran, ZHANG Zhipeng, ZHAO Jun. Evaluation of subway station flood safety resilience based on H-OWA operator and projection pursuit [J]. China Safety Science Journal, 2023, 33(4): 148-154.
[6]	ZHOU Shijie, LIU Donghai, JIN Rui. Multi-evidence fusion comprehensive evaluation of importance of safety accident causation in hydropower project construction [J]. China Safety Science Journal, 2023, 33(3): 103-110.
[7]	HUANG Xin, TAN Chengsong, WU Kun, QI Lin, CHEN Yu. Study on resilience of airport infrastructure under blizzard weather [J]. China Safety Science Journal, 2023, 33(12): 198-205.
[8]	WU Aizhi. Large-space virtual reality-based emergency drill training system for road transportation accidents of hazardous chemicals [J]. China Safety Science Journal, 2022, 32(S1): 189-196.
[9]	LI Jingqiang, FAN Tianchen. Safety inspection ability model of statutory self-inspection personnel in civil aviation [J]. China Safety Science Journal, 2022, 32(7): 7-13.
[10]	CAO Yuan, YU Xiao, SUN Yongkui. Research on safety headway control of GTS based on intersection condition evaluation [J]. China Safety Science Journal, 2022, 32(6): 144-150.
[11]	HUANG Yajiang, LI Shuquan, LI Yixin, ZHENG Han. Comprehensive evaluation on subway operation safety resilience based on DEMATEL-ISM-ANP [J]. China Safety Science Journal, 2022, 32(6): 171-177.
[12]	XIONG Yu, KONG Dezhong, YANG Shengli, WU Guiyi, ZUO Yujun, CHENG Zhanbo. Cloud model identification of coal face stability in steeply inclined working faces [J]. China Safety Science Journal, 2022, 32(3): 144-151.
[13]	YANG Tianzi, WANG Tieli, PENG Hengming, DUAN Hailin. Evaluation on emergency response vulnerability for work safety accidents in small and micro enterprises [J]. China Safety Science Journal, 2021, 31(12): 176-183.
[14]	JIANG Tao, ZHANG Yulong, LI Shibo, LI Zheng, QIU Hailiang. Research on comprehensive performance evaluation system of large multi-functional rescue attachments [J]. China Safety Science Journal, 2021, 31(1): 102-108.
[15]	ZHU Guanji, LIU Di, SUN Qiang, ZHOU Zichao. Evaluation on occupational safety adaptability of railway locomotive drivers [J]. China Safety Science Journal, 2020, 30(S1): 64-70.