隧道衬砌自动化检测及健康评价技术研究

蒋宇静; 张学朋

doi:10.3973/j.issn.2096-4498.2021.03.001

隧道建设 >

2021 , Vol. 41 >Issue 3: 341 - 348

DOI: https://doi.org/10.3973/j.issn.2096-4498.2021.03.001

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隧道衬砌自动化检测及健康评价技术研究

蒋宇静 ,
张学朋

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（1. 矿山灾害预防控制省部共建国家重点实验室(培育)（山东科技大学），山东青岛 266590； 2. 长崎大学工学院，日本长崎 8528521）

蒋宇静（1962—），男，江苏靖江人，1993年毕业于日本国立九州大学，岩土工程专业，博士，教授，日本工程院外籍院士，现从事隧道及地下空间灾害防控理论与技术研究工作。E-mail： jiangyjcn@gmail.com。*通信作者：张学朋， E-mail: zhangxuepeng0722@126.com。

网络出版日期: 2021-04-02

基金资助

山东省自然科学基金（ZR2020QE270）；浙江省岩石力学与地质灾害重点实验室开放基金(ZJRMG-2020-03)

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Research on Automatic Detection and Health Assessment of Tunnel Lining

JIANG Yujing ,
ZHANG Xuepeng

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(1. State Key Laboratory of Mining Disaster Prevention and Control Cofounded by Shandong Province and the Ministry 
of Science and Technology (Shandong University of Science and Technology), Qingdao 266590, Shandong, China;  2. Graduate School of Engineering, Nagasaki University, Nagasaki 8528521, Japan)

Online published: 2021-04-02

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摘要

为进一步提高隧道衬砌的自动化检测及健全度评价技术，基于无损检测技术开展了非可视化高速摄影检测技术和常时微动检测技术研究。非可视化高速摄影检测技术能够实现衬砌表面病害高速检测、自动识别与提取，检测系统行车速度可达到100 km/h，裂缝检测精度可达到0.2 mm (检测车速度100 km/h)；常时微动检测技术能够实现提取隧道衬砌内部异常点（包括裂缝和空洞）的自动检测，具有小型化、抗干扰能力强、精度高、无需额外震源等优势。健全度评价方面，提出分形维数、常时微动平均合成谱RAS (resultant average spectrum)，结合TCI(tunnellining crack index)实现隧道衬砌病害特征的定量化描述，3个指标可以综合考虑裂缝的宽度、长度、方向、数量、交叉分布以及衬砌内部异常等特性，相互结合可以更为准确地确定损伤衬砌段。

关键词： 隧道; 衬砌病害; 自动化检测; 非可视化高速摄影; 常时微动检测; 健康评价

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蒋宇静 , 张学朋 . 隧道衬砌自动化检测及健康评价技术研究[J]. 隧道建设, 2021 , 41(3) : 341 -348 . DOI: 10.3973/j.issn.2096-4498.2021.03.001

Abstract

Aiming at advancing the automatic detection and health assessment technology for the tunnel lining, nonvisual highspeed photogrammetry and microtremor measurement technology are introduced on the basis of the nondestructive detection technology of tunnellining diseases. The nonvisual highspeed photogrammetry technology can automatically identify and extract the lining surface defect with a highcrack width resolution of 0.2 mm under a detection driving velocity of 100 km/h, whereas, the microtremor measurement technology can automatically detect the inner abnormal points (including cracks and cavities) of a tunnel lining. The measurement equipments are characterized by miniaturization, strong antiinterference, high resolution, and nonextra exciting power requirements. Moreover, the fractal dimension and averaged synthetic spectrum resultant average spectrum of a microtremor are proposed, and combining with the tunnellining crack index, the quantitative assessment of a health condition can be provided. These three indices can comprehensively represent the characteristics of width, length, crack direction, number, and the distribution of cracks and inner abnormal points of a tunnel lining, determining the damaged lining section with high accuracy.

Key words： tunnel; lining disease; automatic detection; nonvisual high ; speed photogrammetry technology; microtremor measurement technology; health assessment

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