TY - JOUR
T1 - Image-based 3D reconstruction for rail profile measurement
AU - Zhang, Dongyu
AU - Lingamanaik, Siva N.
AU - Chung, Hoam
N1 - Funding Information:
The first and the third authors appreciate the support from Monash Institute of Railway Technology in this project. The authors acknowledge the financial support provided by the Rail Manufacturing Cooperative Research Centre under R3.7.8.
Publisher Copyright:
© IMechE 2022.
PY - 2023/3
Y1 - 2023/3
N2 - The routine inspection of railheads for defects such as wear and surface cracks is a tedious process, which, if not detected, can alter the wheel-rail contact interaction leading to catastrophic events. This study investigates and implements a railhead measurement method using image-based three-dimensional reconstruction, which enables rapid scanning of railheads and production of detail cross-sectional measurements for rail-wheel interface analysis. A complete workflow with a methodology for reconstructing railheads from images and extracting cross-sectional measurements from the reconstructed model is presented. In order to validate the proposed method in the field, a mobile automated system was equipped with an array of cameras specifically spaced to cover the areas of interest on the railhead. The system can automatically transverse along the railhead, acquiring images synchronously. Two case studies in the laboratory environment and the real railway site have been performed to evaluate the performance and accuracy against industry practices. The results show that the proposed method can accurately measure the railhead cross-sectional profile at an root mean square error (RMSE) less than 0.3 mm compared with MiniProf. Furthermore, continuous cross-sectional data and intuitive color information are provided by our method which can help inspectors to locate defects easily and more efficiently.
AB - The routine inspection of railheads for defects such as wear and surface cracks is a tedious process, which, if not detected, can alter the wheel-rail contact interaction leading to catastrophic events. This study investigates and implements a railhead measurement method using image-based three-dimensional reconstruction, which enables rapid scanning of railheads and production of detail cross-sectional measurements for rail-wheel interface analysis. A complete workflow with a methodology for reconstructing railheads from images and extracting cross-sectional measurements from the reconstructed model is presented. In order to validate the proposed method in the field, a mobile automated system was equipped with an array of cameras specifically spaced to cover the areas of interest on the railhead. The system can automatically transverse along the railhead, acquiring images synchronously. Two case studies in the laboratory environment and the real railway site have been performed to evaluate the performance and accuracy against industry practices. The results show that the proposed method can accurately measure the railhead cross-sectional profile at an root mean square error (RMSE) less than 0.3 mm compared with MiniProf. Furthermore, continuous cross-sectional data and intuitive color information are provided by our method which can help inspectors to locate defects easily and more efficiently.
KW - 3D reconstruction
KW - rail inspection
KW - Rail profile measurement
UR - http://www.scopus.com/inward/record.url?scp=85132934648&partnerID=8YFLogxK
U2 - 10.1177/09544097221110322
DO - 10.1177/09544097221110322
M3 - Article
AN - SCOPUS:85132934648
SN - 0954-4097
VL - 237
SP - 309
EP - 321
JO - Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit
JF - Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit
IS - 3
ER -