Statistical methods for critical scenarios in aeronautics

Houssam Alrachid 1 Virginie Ehrlacher 1, 2 Alexis Marceau 3 Karim Tekkal 4
ENPC - École des Ponts ParisTech, CERMICS - Centre d'Enseignement et de Recherche en Mathématiques et Calcul Scientifique, Inria Paris-Rocquencourt
Abstract : We present numerical results obtained on the CEMRACS project Predictive SMS proposed by Safety Line. The goal of this work was to elaborate a purely statistical method in order to reconstruct the deceleration profile of a plane during landing under normal operating conditions, from a database containing around $1500$ recordings. The aim of Safety Line is to use this model to detect malfunctions of the braking system of the plane from deviations of the measured deceleration profile of the plane to the one predicted by the model. This yields to a multivariate nonparametric regression problem, which we chose to tackle using a Bayesian approach based on the use of gaussian processes. We also compare this approach with other statistical methods.
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Contributor : Houssam Alrachid <>
Submitted on : Friday, September 5, 2014 - 3:48:38 PM
Last modification on : Friday, May 25, 2018 - 12:02:07 PM

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  • HAL Id : hal-01061369, version 1
  • ARXIV : 1409.1446


Houssam Alrachid, Virginie Ehrlacher, Alexis Marceau, Karim Tekkal. Statistical methods for critical scenarios in aeronautics. 2014. ⟨hal-01061369⟩



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