Identification of train loads from the dynamic responses of an integrated sleeper in situ - École des Ponts ParisTech
Article Dans Une Revue Journal of Intelligent Material Systems and Structures Année : 2020

Identification of train loads from the dynamic responses of an integrated sleeper in situ

Identification des chargements exercés par le train à partir des réponses dynamiques d'une traverse instrumentée

Le Hung Tran
Tien Hoang
Gilles Forêt
Denis Duhamel
Samir Messad
Arnaud Loaec
  • Fonction : Auteur

Résumé

The monitoring of railway tracks can be performed through several measurement techniques. Recently, a method of diagnosing the railway track has been proposed using fiber Bragg gratings integrated inside the railway sleeper. An analytical model for the dynamics of railway sleepers has been developed allowing calculation of the sleeper responses. In this model, using the relation between the rail forces and displacements of a periodically supported beam, the sleeper's dynamic equation is written with the help of the Euler-Bernoulli beam and Dirac's delta distribution. Subsequently, the sleeper dynamic responses are calculated using the Green's function. This article presents an application of this model to identify the train loads from the strains measured in situ. Based on this model, we can obtain a matrix which presents the link between the loads and the sleeper responses. Then, by substituting the Fourier transform of measured strains at the middle and at the two rail seats of the sleeper, the train loads can be quickly calculated by inverting the matrix with the help of MATLAB. This method is validated by the experiments. Numerical examples with the measurement in situ are presented to show identified wheel loads from experimental signals.
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Dates et versions

hal-02870487 , version 1 (25-06-2020)

Identifiants

Citer

Le Hung Tran, Tien Hoang, Gilles Forêt, Denis Duhamel, Samir Messad, et al.. Identification of train loads from the dynamic responses of an integrated sleeper in situ. Journal of Intelligent Material Systems and Structures, 2020, pp.1045389X2092290. ⟨10.1177/1045389X20922905⟩. ⟨hal-02870487⟩
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