铁路基础设施复杂施工场景感知数据集

面向铁路隧道钻爆法施工全过程，聚焦隧道开挖、初期支护与二次衬砌等关键工序，系统性整合全站仪、三维激光扫描仪及工业相机等多源感知设备，应用智能型凿岩台车和隧道超欠挖智能诊断机器人等装备，对复杂施工场景进行高精度、多模态数据采集与融合预处理。通过构建涵盖点云、图像与地质素描等多维异构数据的数据集，描述隧道施工动态演化过程中的几何形态、结构特征与围岩响应，从而为铁路隧道施工质量自动诊断提供了坚实的数据基底与理论支撑，助力推动基础设施建设向数字化、智能化转型。Focusing on the entire construction process of railway tunnels constructed via the drill-and-blast method, this work centers on key procedures including tunnel excavation, primary support, and secondary lining. It systematically integrates multi-source sensing equipment such as total stations, 3D laser scanners, and industrial cameras, and applies specialized equipment like intelligent jumbo drills and intelligent tunnel overbreak/underbreak diagnosis robots to conduct high-precision, multi-modal data collection and fusion preprocessing for complex construction scenarios. By building a dataset containing multi-dimensional heterogeneous data including point clouds, images, and geological sketches, this work describes the geometric morphology, structural features, and surrounding rock responses during the dynamic evolution of tunnel construction. It thus provides a solid data foundation and theoretical support for the automatic diagnosis of railway tunnel construction quality, and facilitates the digital and intelligent transformation of infrastructure construction.

搜集汇总

背景与挑战

背景概述

该数据集面向铁路隧道钻爆法施工全过程，整合多源感知设备和智能装备，采集并融合了点云、图像与地质素描等多维异构数据，以描述施工动态演化中的几何形态、结构特征与围岩响应。它为铁路隧道施工质量自动诊断提供了数据支撑，旨在推动基础设施建设的数字化与智能化转型。