135 articles – 87 Notices  [english version]

hal-00488946, version 1

Trajectory Clustering for Vibration Detection in Aircraft Engines

Aurélien Hazan () 1, Michel Verleysen () 2, Marie Cottrell () 1, Jérôme Lacaille 3

Industrial Conference on Data mining 2010 (2010) 362-375

Résumé : The automatic detection of the vibration signature of rotating parts of an aircraft engine is considered. This paper introduces an algorithm that takes into account the variation over time of the level of detection of orders, i.e. vibrations ate multiples of the rotating speed. The detection level over time at a specific order are gathered in a so-called trajectory. It is shown that clustering the trajectories to classify them into detected and non-detected orders improves the robustness to noise and other external conditions, compared to a traditional statistical signal detection by an hypothesis test. The algorithms are illustrated in real aircraft engine data.

  • 1 :  Statistique, Analyse et Modélisation Multidisciplinaire (SAmos-Marin Mersenne) (SAMM)
  • Université Paris I - Panthéon-Sorbonne
  • 2 :  MachineLearning Group - DICE (DICE)
  • Université Catholique de Louvain (UCL) - Belgique
  • 3 :  SNECMA Villaroche [Moissy-Cramayel]
  • Safran Group
  • Collaboration : Snecma
  • Domaine : Statistiques/Applications
 
  • hal-00488946, version 1
  • http://hal.archives-ouvertes.fr/hal-00488946
  • oai:hal.archives-ouvertes.fr:hal-00488946
  • Contributeur : Aurélien Hazan <>
  • Soumis le : Jeudi 3 Juin 2010, 14:48:08
  • Dernière modification le : Mardi 17 Janvier 2012, 16:42:50