Frequency-Dependent Peak-Over-Threshold algorithm for fault detection in the spectral domain

Aurélien Hazan 1 Kurosh Madani 1
1 SYNAPSE
LISSI - Laboratoire Images, Signaux et Systèmes Intelligents
Abstract : An original novelty detection algorithm in the Fourier domain, using extreme value theory (EVT) is considered in this article. Periodograms may be considered as frequency-dependent random vari- ables, and this can be taken into account when designing statistical tests. Frequency-Dependent Peak-Over-Threshold (FDPOT) puts special em- phasis on the frequency dependence of extreme value statistics, thanks to Vector Generalized Additive Models (VGAM) estimation. An application is discussed in the field of mechanical vibrations. It is first shown that performance increases compared to POT detection. Then FDPOT is compared to state-of-the-art algorithms such as KPCA.
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Contributor : Aurélien Hazan <>
Submitted on : Monday, April 29, 2013 - 10:24:12 AM
Last modification on : Friday, October 4, 2019 - 1:28:02 AM
Long-term archiving on : Tuesday, July 30, 2013 - 4:30:08 AM

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Aurélien Hazan, Kurosh Madani. Frequency-Dependent Peak-Over-Threshold algorithm for fault detection in the spectral domain. Proc. Of the 21th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning, ESANN2013, Apr 2013, Bruges, Belgium. ⟨hal-00785382v2⟩

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