Examinando por Materia "superstructure"

Mostrando 1 - 2 de 2
  • No hay miniatura disponible
    Ítem
    Detection of structural damage and estimation of reliability using a multidimensional monitoring approach
    (SAGE PUBLICATIONS LTD, 2018-04-01) Ortiz J.O.; Betancur G.R.; Gómez J.; Castañeda L.F.; Zajsc G.; Gutiérrez-Carvajal R.E.; Universidad EAFIT. Departamento de Ingeniería Mecánica; Estudios en Mantenimiento (GEMI)
    Many structural elements are exposed to load conditions that are difficult to model during the design phase, such as environmental uncertainties, random impacts, and overloading, amongst others, thus increasing unprogrammed maintenance and reducing confidence in the reliability of the structure in question. One way to deal with this problem is to monitor the structural condition of the element. This approach requires supervising several signals coming from critical locations and then performing an accurate condition estimation of the element in question based on the data collected. This study implements a method to diagnose and evaluate the reliability of the bolster beam structure of the railway vehicle during a fatigue test. The results show that multidimensional monitoring not only diagnoses the element accurately but also results in correct estimation of reliability. © 2017, © IMechE 2017.
  • No hay miniatura disponible
    Ítem
    A fractional Fourier transform-based method to detect impacts between the bogie and the car body of a railway vehicle: A data-driven approach
    (SAGE PUBLICATIONS LTD, 2018-01-01) Gutierrez-Carvajal, R. E.; Betancur, German R.; Castaneda, Leonel F.; Zajac, G.; Universidad EAFIT. Departamento de Ingeniería Mecánica; Estudios en Mantenimiento (GEMI)
    Structural railway transport elements are typically designed to work for at least 30 years without undergoing major maintenance. However, real-life operational conditions present behaviors different to the model predicted during the initial design phase, which affects the lifetime of the elements in question. This is the case of first-generation railway vehicles which operates in the city of Medellín, Colombia, as the bolster beam presented cracks after 12 years of operation, possibly due to undesired impacts between the bogie and the pivot of the bolster beam. Monitoring vibrational signals would give some sort of an insight into impact phenomena; however, herein lies the problem, as they are difficult to identify using only vibration signals, occurring during time events that take place in a speed-varying system. In this article, the authors present a technique that automatically detects impacts using multiple in-between time/frequency representations, ranking them according to their capacity to discriminate between impact events. Our results show that the best representation for this data was the Fractional Cepstrum Transform at order 0.5 (auROC = 0.961), which outperformed the best pure domain descriptor by least 4%. © 2016, © IMechE 2016.