Abstract
The purpose of this paper is to conduct a feasibility study to examine defects of turnouts using three-dimensional scanning. The turnout defect detection tools are rare and expensive. Three-dimensional scan of a new and a damaged turnout using Kinect device has been taken. Since the boundary condition in each turnout blade is different, image processing algorithm should begin with noise reduction and then find the damage location comparing the new and the damaged sample. Moreover, failure mode and effects analysis approach have been used for risk analysis. This method indicates the maintenance priority for each turnout. As a result, risk priority number calculated for maintenance management relies on reliability derived for each equipment. By this means, resource planning and maintenance system are optimized. Finally, failure forecasting related to local condition is possible.
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Ebadi, M., Bagheri, M., Lajevardi, M.S., Haas, B. (2019). Defect Detection of Railway Turnout Using 3D Scanning. In: Fraszczyk, A., Marinov, M. (eds) Sustainable Rail Transport. Lecture Notes in Mobility. Springer, Cham. https://doi.org/10.1007/978-3-319-78544-8_1
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