Frequency Analysis of the Railway Track under Loads Caused by the Hunting Phenomenon

Gerardo Hurtado-Hurtado, Luis Morales-Velazquez, Martín Valtierra-Rodríguez, Frank Otremba and Juan C. Jáuregui-Correa
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Gerardo Hurtado-Hurtado: Faculty of Engineering, Autonomous University of Queretaro, Campus San Juan del Río, San Juan del Rio 76807, Mexico
Luis Morales-Velazquez: Faculty of Engineering, Autonomous University of Queretaro, Campus San Juan del Río, San Juan del Rio 76807, Mexico
Martín Valtierra-Rodríguez: Faculty of Engineering, Autonomous University of Queretaro, Campus San Juan del Río, San Juan del Rio 76807, Mexico
Frank Otremba: Federal Institute for Materials Research and Testing (BAM), 12489 Berlin, Germany
Juan C. Jáuregui-Correa: Faculty of Engineering, Autonomous University of Queretaro, Santiago de Queretaro 76010, Mexico

Mathematics, 2022, vol. 10, issue 13, 1-17

Abstract: Hunting is a potentially dangerous phenomenon related to the lateral oscillation of the wheels that impacts the rails and causes the wear of the infrastructure’s components. Therefore, the analysis and timely detection of hunting can lead to the application of corrective maintenance tasks, reducing damages, and costs and even derailments as a result. In this work, the vibration response of a finite element model of a rail with hunting-induced loads by a single wheel is analyzed in three directions: longitudinal, lateral, and vertical. The contact patch forces are calculated by means of Simpack ® using the Kalker linear theory and the contact Hertz theory. The system is solved by using the Newmark-β approach. The results of the deflection and vibration analysis, following the proposed methodology, show how the different characteristics of the loads impact the rail.

Keywords: continuous wavelet transform; empirical mode decomposition; finite element method; frequency analysis; hunting phenomenon; mechanical modelling; rail vibrations (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2022
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