Railway Vehicle Wheel Flat Detection with Multiple Records Using Spectral Kurtosis Analysis
| Autor: | P.A. Montenegro, Araliya Mosleh, Pedro Alves Costa, Rui Calçada |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Technology
Computer science QH301-705.5 QC1-999 020101 civil engineering railway vehicles 02 engineering and technology Accelerometer Track (rail transport) Automotive engineering 0201 civil engineering wheel flat detection Acceleration 0203 mechanical engineering wayside condition monitoring systems General Materials Science Sensitivity (control systems) Biology (General) multisensor array Instrumentation QD1-999 Strain gauge Fluid Flow and Transfer Processes Computer simulation Process Chemistry and Technology Physics General Engineering Engineering (General). Civil engineering (General) Computer Science Applications Chemistry 020303 mechanical engineering & transports spectral kurtosis analysis Train TA1-2040 Envelope (motion) |
| Zdroj: | Applied Sciences, Vol 11, Iss 4002, p 4002 (2021) Applied Sciences Volume 11 Issue 9 |
| ISSN: | 2076-3417 |
| Popis: | The gradual deterioration of train wheels can increase the risk of failure and lead to a higher rate of track deterioration, resulting in less reliable railway systems with higher maintenance costs. Early detection of potential wheel damages allows railway infrastructure managers to control railway operators, leading to lower infrastructure maintenance costs. This study focuses on identifying the type of sensors that can be adopted in a wayside monitoring system for wheel flat detection, as well as their optimal position. The study relies on a 3D numerical simulation of the train-track dynamic response to the presence of wheel flats. The shear and acceleration measurement points were defined in order to examine the sensitivity of the layout schemes not only to the type of sensors (strain gauge and accelerometer) but also to the position where they are installed. By considering the shear and accelerations evaluated in 19 positions of the track as inputs, the wheel flat was identified by the envelope spectrum approach using spectral kurtosis analysis. The influence of the type of sensors and their location on the accuracy of the wheel flat detection system is analyzed. Two types of trains were considered, namely the Alfa Pendular passenger vehicle and a freight wagon. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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