Print Email Facebook Twitter Evaluation of the influential parameters contributing to the reconstruction of railway wheel defect signals Title Evaluation of the influential parameters contributing to the reconstruction of railway wheel defect signals Author Alemi, A. (TU Delft Transport Engineering and Logistics) Corman, Francesco (ETH Zürich) Pang, Y. (TU Delft Transport Engineering and Logistics) Lodewijks, Gabriel (University of New South Wales) Date 2019 Abstract A wheel impact load detector is used to assess the condition of a railway wheel by measuring the dynamic forces generated by defects. This system normally measures the impact force at multiple points by exploiting multiple sensors to collect samples from different portions of the wheel circumference. The outputs of the sensors are used to estimate the dynamic force as the main indicator for detecting the presence of the defect. This method fails to identify the defect type and its severity. Recently, a data fusion method has been developed to reconstruct the wheel defect signal from the wheel–rail contact signals measured by multiple wayside sensors. The reconstructed defect signal can be influenced by different parameters such as train velocity, axle load, number of sensors, and wheel diameter. This paper aims to carry out a parametric study to investigate the influence of these parameters. For this purpose, VI-Rail is used to simulate the wheel–rail interaction and provide the required data. Then, the developed fusion method is exploited to reconstruct the defect signal from the simulated data. This study provides a detailed insight into the effects of the influential parameters by investigating the variation of the reconstructed defect signals. Subject condition monitoringcontactdefectparametric studyRailway wheelsignal reconstruction To reference this document use: http://resolver.tudelft.nl/uuid:dee33599-4373-4896-b807-85f66195be29 DOI https://doi.org/10.1177/0954409719882828 ISSN 0954-4097 Source Institution of Mechanical Engineers. Proceedings. Part F: Journal of Rail and Rapid Transit, 234 (2020) (9), 1005-1016 Part of collection Institutional Repository Document type journal article Rights © 2019 A. Alemi, Francesco Corman, Y. Pang, Gabriel Lodewijks Files PDF 0954409719882828.pdf 1.47 MB Close viewer /islandora/object/uuid:dee33599-4373-4896-b807-85f66195be29/datastream/OBJ/view