Trajectory Clustering for Vibration Detection in Aircraft Engines

  • Aurélien Hazan
  • Michel Verleysen
  • Marie Cottrell
  • Jérôme Lacaille
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6171)


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.


Mutual Information Vibration Signal Aircraft Engine Vibratory Signal Shaft Speed 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Aurélien Hazan
    • 1
  • Michel Verleysen
    • 1
    • 2
  • Marie Cottrell
    • 1
  • Jérôme Lacaille
    • 3
  1. 1.SAMM, Université Paris 1ParisFrance
  2. 2.DICE, Université Catholique de LouvainLouvain-la-NeuveBelgium
  3. 3.SNECMA, Groupe SafranMoissy CramayelFrance

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