具有无序排列管片环结构的地铁盾构隧道数字模型智能重建

Intelligent Reconstruction of the Digital Model of Metro Shield Tunnels with Disordered Erected Segment Ring Structure

运营地铁隧道的管理、健康监测及维护正逐渐趋向于数字化、智能化;但常因地铁盾构隧道管理和检测单位缺少隧道数字模型,限制了地铁隧道智能维护和管理系统的应用和发展。文章针对地铁盾构隧道中无序排列的管片环结构,提出了一种基于深度学习和机器视觉的地铁盾构隧道数字模型智能重建方法,利用检测车获取的隧道衬砌内表面高清图片,对管片特征物(螺栓孔)进行智能识别与自动分类,再根据螺栓孔群的分布特点自动推断隧道管片环的排版规律,从而结合隧道实际线路实现隧道数字模型快速重建。某地铁隧道的实例应用结果表明,该方法适用于管片无规律性错缝拼装的情况,能以100%的准确率实现地铁盾构隧道数字模型的智能重建。

The management, health monitoring and maintenance of operational metro tunnels have been gradually becoming digital and intelligent. However, the lack of digital tunnel models often limits the application and development of intelligent maintenance and management systems for metro shield tunnel management and inspection organizations. This paper proposes an intelligent reconstruction method of the digital model of disordered erected segment ring structure in metro shield tunnels based on deep learning and machine vision, uses high-definition pictures of the inner surface of the tunnel lining obtained by inspection vehicles to intelligently identify and automatically classify the tunnel segment features(bolt holes), and then automatically infers the layout pattern of the tunnel segment rings according to the distribution characteristics of the bolt hole groups, thus achieving rapid reconstruction of the tunnel digital model by combining with the actual tunnel alignment. The application case in a certain metro tunnel shows that the proposed method is applicable to shield tunnels with irregularly and staggered erected segments, and can achieve the intelligent reconstruction of the digital model of the metro shield tunnel with 100% accuracy.