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Linear smoothing of FRF for aicraft engine vibration monitoring

Abstract : 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
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Contributor : Aurélien Hazan <>
Submitted on : Wednesday, October 6, 2010 - 11:15:37 AM
Last modification on : Tuesday, January 19, 2021 - 11:08:38 AM
Long-term archiving on: : Friday, January 7, 2011 - 2:45:31 AM


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  • HAL Id : hal-00523747, version 1


Aurélien Hazan, Michel Verleysen, Marie Cottrell, Jérôme Lacaille. Linear smoothing of FRF for aicraft engine vibration monitoring. International Conference on Noise and Vibration Engineering, Sep 2010, Leuven, Belgium. ID126, ⟨hal-00523747⟩



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