| 激光扫描盾构隧道断面变形快速检测 |
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| 引用本文： | 刘新根,陈莹莹,刘学增.激光扫描盾构隧道断面变形快速检测[J].交通运输工程学报,2021,21(2):107-116. |
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| 作者姓名： | 刘新根 陈莹莹 刘学增 |
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| 作者单位： | 1.上海同岩土木工程科技股份有限公司，上海 2000922.上海地下基础设施安全检测与养护装备工程技术研究中心，上海 2000923.同济大学 土木信息技术教育部工程研究中心，上海 200092 |
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| 基金项目： | 国家重点研发计划项目2018YFB2101004国家自然科学基金项目41827807 |
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| 摘 要： | 针对人工检测效率低、变形检测车定位不准、噪点剔除困难、数据处理滞后等技术难题，基于盾构隧道管片环缝灰度图像数学形态特征，通过图像滑窗方式，利用直方图均衡化、缩放、阈值判定等方法快速自动识别环缝，并依据环缝已知位置反向修正隧道里程; 基于距离最小二乘法椭圆曲线拟合，建立了盾构隧道激光扫描噪点三次迭代自动剔除方法; 通过对管片环上各单环激光扫描数据拟合椭圆进行均值处理，并与隧道设计参数或上次检测结果比对，确定了隧道断面变形; 以轨检小车为载体，集成断面三维激光扫描仪、倾角仪、编码器、测距轮和计算机等设备，研制了盾构隧道断面变形快速检测车，开发了配套的数据采集和处理软件，并进行了工程试验和实际应用。研究结果表明:检测时速为5 km·h-1时，检测车系统隧道内水平和垂直方向直径复测差值绝对值小于2 mm的占比分别为98.41%和96.21%，小于1 mm的占比分别为82.36%和71.92%，系统复测精度为2 mm，多数可达到1 mm，说明环缝识别、噪点剔除、整环收敛变形算法和检测系统具有较高的稳定性和重现性; 检测车可自动采集和处理数据，检测作业后24 h可输出检测分析报告，结果准确可靠，可为盾构隧道结构健康评定和养护提供参考。
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| 关 键 词： | 盾构隧道 变形检测 激光扫描 最小二乘法 椭圆拟合 噪点剔除 |
| 收稿时间： | 2020-10-11 |
Laser scanning-based rapid detection of deformation of shield tunnel section |
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| LIU Xin-gen,CHEN Ying-ying,LIU Xue-zeng.Laser scanning-based rapid detection of deformation of shield tunnel section[J].Journal of Traffic and Transportation Engineering,2021,21(2):107-116. |
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| Authors: | LIU Xin-gen CHEN Ying-ying LIU Xue-zeng |
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| Affiliation: | 1.Shanghai Tongyan Civil Engineering Technology Co., Ltd., Shanghai 200092, China2.Shanghai Engineering Research Center of Detecting Equipment for Underground Infrastructure, Shanghai 200092, China3.Engineering Research Center of Civil-Informatics of Ministry of Education, Tongji University, Shanghai 200092, China |
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| Abstract: | In view of existing technical problems such as low efficiency of manual detection, inaccurate positioning of deformation detection vehicle, difficulty in noise elimination and lag of data processing, a rapid automatic method to identify circumferential seams was proposed based on mathematical morphological characteristics of grayscale images of shield tunnel segment circumferential seams of and image sliding windows. The proposed method includes histogram equalization, scaling, and threshold determination. In addition, the tunnel mileage was reversely corrected according to the known positions of circumferential seams. Based on the ellipse curve fitting by the distance least square method, a three-fold iteration method for the automatic elimination of laser scanning noise in shield tunnels was established. The fitting ellipses for the single-ring laser scanning data of segment rings were subjected to the mean value processing. The results were compared with the tunnel design parameters or the last test results to identify the deformation along the tunnel section. A rapid detection vehicle to identify the deformation along the shield tunnel section was built by installing the 3D laser scanner, inclinometer, encoder, ranging wheel, computer, and other equipment. The supporting data acquisition and processing software were also developed, and the engineering experiment and practical application were conducted. Research result indicates that when the detection speed is 5 km·h-1, 98.41% and 96.21% of the absolute differences between repeat measurements of horizontal and vertical diameters of tunnel by the detection vehicle system are less than 2 mm, respectively. 82.36% and 71.92% of the absolute differences are less than 1 mm, respectively. The repeat measurements accuracy of the system is 2 mm, most of which can reach 1 mm. This shows that the circumferential seam identification, noise elimination, whole ring convergence deformation algorithm and detection system have high stability and reproducibility. The detection vehicle can automatically collect and process data. The test analysis report can be output 24 h after the detection. The results are accurate and reliable. They can provide references for the health evaluation and maintenance of shield tunnel structures. 2 tabs, 22 figs, 30 refs. |
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