Print Email Facebook Twitter Evaluating degradation at railway crossings using axle box acceleration measurements Title Evaluating degradation at railway crossings using axle box acceleration measurements Author Wei, Z. (TU Delft Railway Engineering) Nunez, Alfredo (TU Delft Railway Engineering) Li, Z. (TU Delft Railway Engineering) Dollevoet, R.P.B.J. (TU Delft Railway Engineering) Date 2017-09-29 Abstract In this paper, we investigate the capability of an axle box acceleration (ABA) system to evaluate the degradation at railway crossings. For this purpose, information from multiple sensors, namely, ABA signals, 3D rail profiles, Global Positioning System (GPS) and tachometer recordings, was collected from both nominal and degraded crossings. By proper correlation of the gathered data, an algorithm was proposed to distinguish the characteristic ABA related to the degradation and then to evaluate the health condition of crossings. The algorithm was then demonstrated on a crossing with an unknown degradation status, and its capability was verified via a 3D profile measurement. The results indicate that the ABA system is effective at monitoring two types of degradations. The first type is uneven deformation between the wing rail and crossing nose, corresponding to characteristic ABA frequencies of 230–350 and 460–650 Hz. The second type is local irregularity in the longitudinal slope of the crossing nose, corresponding to characteristic ABA frequencies of 460–650 Hz. The types and severity of the degradation can be evaluated by the spatial distribution and energy concentration of the characteristic frequencies of the ABA signals. Subject 3D profile measurementAxle box acceleration measurementCrossing degradationRailway infrastructure monitoringOA-Fund TU Delft To reference this document use: http://resolver.tudelft.nl/uuid:5094ce93-3e6c-465a-8b1d-c350e3c59c76 DOI https://doi.org/10.3390/s17102236 ISSN 1424-8220 Source Sensors, 17 (10), 1-16 Part of collection Institutional Repository Document type journal article Rights © 2017 Z. Wei, Alfredo Nunez, Z. Li, R.P.B.J. Dollevoet Files PDF sensors_17_02236.pdf 9.38 MB Close viewer /islandora/object/uuid:5094ce93-3e6c-465a-8b1d-c350e3c59c76/datastream/OBJ/view