Linear smoothing of FRF for aicraft engine vibration monitoring

Aurélien Hazan; Michel Verleysen; Marie Cottrell; Jérôme Lacaille

hal-00523747, version 1

Linear smoothing of FRF for aicraft engine vibration monitoring

Aurélien Hazan ( Auteur à contacter de préférence ) ¹, Michel Verleysen () ^1, 2, Marie Cottrell () ¹, Jérôme Lacaille () ³

International Conference on Noise and Vibration Engineering (2010) ID126, http://www.isma-isaac.be/publications/

Résumé : The problem of aircraft engine condition monitoring based on vibration signals is addressed. To do so, we compare two estimators of the Frequency Response Function of an aircraft engine which input is its shaft angular position and which output is an accelerometric signal that measures vibrations. It is shown that this problem can be seen as a smoothing problem, and that linear kernel smoothing such as Gaussian Process Regression allows the computation of the FRF

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

hal-00523747, version 1
http://hal.archives-ouvertes.fr/hal-00523747
oai:hal.archives-ouvertes.fr:hal-00523747
Contributeur : Aurélien Hazan <>
Soumis le : Mercredi 6 Octobre 2010, 11:15:37
Dernière modification le : Mardi 17 Janvier 2012, 16:39:33

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