Analysis of Maintenance Techniques for a Three-Dimensional Digital Twin-Based Railway Facility with Tunnels

Abstract

In accordance with the paradigm of the 4th and Industrial Revolution, the introduction of building information modeling is expected in all areas related to railroad construction, operation and management, along with the establishment of a metaverse platform that combines big data, the Internet of Things, and artificial intelligence. The performance of tasks related to the safety and maintenance of railway facilities is aided by the use of digital systems free from physical and temporal constraints. Three-dimensional (3D) modeling and other 4th industrial technologies, such as unmanned aerial vehicles (UAVs) and light detection and ranging (LiDAR), are increasingly implemented in many types of infrastructure. With respect to railroads, the use of these methods to monitor tunnel spaces has been hindered by the limitations of modeling with UAV and inadequate Global Positioning System reception. Here, we conducted the domestic application of 4th industrial technologies to a railway tunnel; we addressed these problems using a BLK360, a fixed LiDAR device that combines two-dimensional panoramic images and a 3D point cloud method. The outcomes of this research will benefit railway operation managers by providing a platform combining a two-dimensional panoramic virtual reality (VR) image and a 3D model developed from a 3D scan framework for the maintenance of existing railway facilities (tunnels). Our approach was optimized for the maintenance and operational management of railroad facilities, as demonstrated for tunnels, because it continuously acquires time-series data that is appropriate for the maintenance of the corresponding space. In the future, this approach can be used for test tracks and operational lines.