铁道科学与工程学报2025，Vol.22Issue(3)：1357-1368,12.DOI:10.19713/j.cnki.43-1423/u.T20240800
基于机器视觉的盾尾间隙智能检测方法研究
Intelligent detection method of shield tail clearance based on machine vision
摘要
Abstract
The shield tail clearance provides crucial data for adjustments in shield tunneling posture and selection of segment assembly point.Manual measurement of shield tail clearance during shield construction is often challenging and imprecise.To address these issues,this article proposed an intelligent detection method that enables real-time measurement of shield tail clearance during construction.A visual scanning system mounted on the rotary mechanism of the assembly machine captures point cloud data of the segments and shield tail.Following the filtering and denoising of the point cloud data,the point cloud of the segment's handhole area was extracted to determine the inspection position for the shield tail clearance.The PSO algorithm was employed to fit the inner arc surface point cloud of the segment to a cylindrical surface,thus accurately determining the segment's axis position.A radial plane,defined by the segment's axis and the shield tail clearance inspection point,was used to extract slices of the segment and shield tail point clouds.An improved least squares method was applied to solve the linear equations of the two point clouds on the obtained slices.The spatial distance between the two lines at the end face of the segment,which was the sum of the shield clearance and the segment thickness,was then calculated.It could determine the shield clearance at the inspection position.This article also explored methods for calculating the shield tail clearance,demonstrating that the PSO algorithm achieves higher accuracy in fitting the cylindrical model to the segment point clouds compared to the non-linear least squares fitting method,thereby more accurately determining the position of the segment axis.By employing the RANSAC algorithm to enhance the traditional least squares method,the accuracy of fitting the intersection line between the plane where the tail clearance was located and the segment or the shield tail was improved,which enhanced the precision of solving the shield tail clearance.Field tests have verified that the shield tail clearance measurement system presented in this article has a repeatability precision better than 1.3 mm and an absolute measurement accuracy better than 2.4 mm,which meets engineering measurement requirements.This research can introduce a novel automated measurement technology for shield tail clearance in shield tunnel construction,promoting the automation and intelligence of shield tunneling construction.关键词
盾尾间隙/智能检测/机器视觉/点云/PSO算法/RANSAC算法Key words
shield tail clearance/intelligent detection/machine vision/point cloud/PSO algorithm/RANSAC algorithm分类
交通工程引用本文复制引用
胡秋斌,毛仁利,庄欠伟,柳献..基于机器视觉的盾尾间隙智能检测方法研究[J].铁道科学与工程学报,2025,22(3):1357-1368,12.基金项目
上海市国资委企业创新发展和能级提升项目(2022020) （2022020）
同济大学学科交叉联合攻关项目(2023-2-ZD-03) （2023-2-ZD-03）
