# Study on Representative Parameters of Reverse Engineering for Maintenance of Ballasted Tracks
## 1 Introduction
Object detection to classify and recognize construction equipment, manpower, and materials, which are the main entities present at earthwork sites, is also being researched by various institutions [14]. In the field of railroad engineering, point clouds-based object detection for tunnels and bridges has also been researched [8; 15]. In this study, the rails, ballast, and sleepers of ballasted track were selected as research subjects. The combined processes of object detection and scan-to-BIM, illustrated in Figure 1, were researched assuming that the maintenance of railroad facilities have been automated. It consists of five steps: (1) collection of point cloud data through 3D scanning; (2) point cloud-based object detection; (3) 3D scan data review using representative parameters for rails, ballast, and sleepers during object detection; (4) linking of railroad BIM library elements corresponding to rails, ballast, and sleepers, based on the object detection results; and (5) construction of a railroad BIM for maintenance. The scope of the current study encompassed two of these steps, i.e., (3) 3D scan data review using representative parameters for rails, ballast, and sleepers during object detection and (4) linking of railroad BIM library elements corresponding to rails, ballast, and sleepers based on the object detection results. Figure 1: Object detection-based Scan-to-BIM process and research scope. This paper is organized as follows: Section 2 describes the methods used in this paper to survey the literature. Section 3 represents selection of the representative parameters on ballasted track. A testbed experiment of the representative parameters on ballasted track are conducted in Section 4. Section 5 concludes this article. As Figure 2 shows, a literature review on RE and object detection was conducted. In addition, acceptance railroad criteria for track irregularities used by the International Union of Railways (UIC), EN, France, Germany, Italy, Austria, US, Japan, and the Republic of Korea were examined. Representative parameters required for damage type identification and 3D object detection of ballasted track were selected based on the review results. A testbed composed of ballast was used to verify the selected representative parameters and acquired point cloud data by 3D scanning, as shown in Figure 2. The values of the representative parameters were measured using the scan data, and a ballasted track BIM model was created. The created ballasted track BIM model and the testbed scanned point cloud data were compared. This compared task has two main key criteria. (1) the representative parameters for the rail, ballast, and sleeper ware identified whether the shape of the ballasted track could be detected. (2) The representative parameters for the rail, ballast, and sleeper ware identified whether the ballasted track damage types described in the literature review could be examined. Finally, based on the testbed results, the shape types of objects that could be distinguished by the representative parameters and the ballasted track damage types that require maintenance were summarized.