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FIRLA Marcin

”Automatic Signal Processing for Wind Turbine Condition Monitoring. Time-Frequency Cropping, Kinematic Association, and All-Sideband Demodulation.”


Directeur de thèse :     Nadine MARTIN

École doctorale :

Spécialité :

Structure de rattachement : Grenoble-INP

Établissement d'origine :

Financement(s) : contrat à durée déterminée ; contrat à durée déterminée


Date d'entrée en thèse : 07/11/2012

Date de soutenance : 21/01/2016


Composition du jury :
Jérôme MARS - Professeur, G-INP, Grenoble, Examinateur, Président du jury
Radoslaw ZIMROZ - Professeur, Wroclaw University of Technology, Pologne, Rapporteur
Mohamed EL BADAOUI - Professeur, Saint Etienne University, Roanne, Rapporteur
Fabien MILLIOZ - Maître de conférences, Lyon 1 University, Lyon, Examinateur
Nadine MARTIN - Directeur de recherche, CNRS, Grenoble, Directrice de thèse
Tomasz BARSZCZ - Professeur, AGH University of Science and Technology, Pologne, Co-directeur de thèse


Résumé : This thesis proposes a three signal-processing methods oriented towards the condition monitoring and diagnosis. In particular the proposed techniques are suited for vibration-based condition monitoring of rotating machinery which works under highly non-stationary operational condition as wind turbines, but it is not limited to such a usage. All the proposed methods are automatic and data-driven algorithms. The first proposed technique enables a selection of the most stationary part of signal by cropping time-frequency representation of the signal. The second method is an algorithm for association of spectral patterns, harmonics and sidebands series, with characteristic frequencies arising from kinematic of a system under inspection. This method features in a unique approach dedicated for rolling-element bearing which enables to overcome difficulties caused by a slippage phenomenon. The third technique is an all-sideband demodulation algorithm. It features in a multi-rate filter and proposes health indicators to facilitate an evaluation of the condition of the investigated system. In this thesis the proposed methods are validated on both, simulated and real-world signals. The presented results show good performance of all the methods.

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