土木与环境工程学报（中英文）2025，Vol.47Issue(5)：77-85,9.DOI:10.11835/j.issn.2096-6717.2024.074
基于多目视觉摄像与图像识别技术的TBM施工隧道围岩结构面识别方法
A method for identifying the structural planes of surrounding rock in TBM construction tunnels based on multi camera vision and image recognition technology
摘要
Abstract
The structural plane of surrounding rock is one of the key geological factors affecting the efficiency and safety of TBM excavation.Developing a rapid,precise,and adaptable method for identifying the structural plane of surrounding rock in TBM tunnels is of great significance.This article proposes a method for identifying rock structure planes based on multi camera vision and image recognition technology.Specifically,based on the equipment using binocular cameras,color and depth images of large exposed surrounding rocks are captured at fixed positions.The depth images are corrected to overcome image distortion issues based on positional parameters such as the position and shooting angle of the binocular camera.Furthermore,the Fine Boundary Description(CED)method was adopted to achieve precise identification of the structural planes of the surrounding rock.This approach is founded on traditional convolutional neural networks and adds a dual path of forward propagation and backward refinement of image data.In the backward refinement path,it continuously strengthens the capture of local boundaries in the image,captures the differences between structural planes and conventional surrounding rock pixels in the image,and then characterizes the boundaries of surrounding rock structural planes.Based on the TBM construction tunnel of Qingdao Metro Line 6,427 sets of color and depth images of the surrounding rock were collected on site.By comparing the model recognition with the actual morphology of cracks,this method was further validated.关键词
全断面岩石隧道掘进机/多目视觉摄像/图像识别/岩体结构面Key words
Tunnel Boring Machine(TBM)/multi camera vision/image recognition/rock structural planes分类
交通工程引用本文复制引用
宋浩天,李宁博,纪宏奎,肖禹航,王银坤,刘彬..基于多目视觉摄像与图像识别技术的TBM施工隧道围岩结构面识别方法[J].土木与环境工程学报（中英文）,2025,47(5):77-85,9.基金项目
山东省自然科学基金(ZR2021QD121)Shandong Provincial Natural Science Foundation(No.ZR2021QD121) （ZR2021QD121）
