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Rafael Gouriveau

Researcher at Centre national de la recherche scientifique

Publications -  81
Citations -  4326

Rafael Gouriveau is an academic researcher from Centre national de la recherche scientifique. The author has contributed to research in topics: Prognostics & Artificial neural network. The author has an hindex of 31, co-authored 81 publications receiving 3252 citations. Previous affiliations of Rafael Gouriveau include Franche Comté Électronique Mécanique Thermique et Optique Sciences et Technologies & University of Franche-Comté.

Papers
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Proceedings Article

PRONOSTIA : An experimental platform for bearings accelerated degradation tests.

Patrick Nectoux, +6 more
TL;DR: In this paper, the authors present an experimental platform called PRONOSTIA, which enables testing, verifying and validating methods related to bearing health assessment, diagnostic and prognostic, which are performed under constant and/or variable operating conditions.
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Enabling Health Monitoring Approach Based on Vibration Data for Accurate Prognostics.

Kamran Javed, +3 more
- 01 Jan 2015 - 
TL;DR: A new approach for feature extraction/selection based on trigonometric functions and cumulative transformation, and the selection is performed by evaluating feature fitness using monotonicity and trendability characteristics, which is applied to the time-frequency analysis of nonstationary signals using a discrete wavelet transform.
Journal ArticleDOI

Particle filter-based prognostics: Review, discussion and perspectives

Marine Jouin, +4 more
- 01 May 2016 - 
TL;DR: The development of the tool in the prognostics field is discussed, current issues are identified, analyzed and some solutions or work trails are proposed, aimed at highlighting future perspectives as well as helping new users to start with particle filters in the goal of progNostics.
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Prognostics of PEM fuel cell in a particle filtering framework

Marine Jouin, +4 more
- 02 Jan 2014 - 
TL;DR: A prognostics framework is proposed that enables avoiding assumptions on the PEMFC behavior, while ensuring good accuracy on RUL estimates, based on a particle filtering approach that enables including non-observable states (degradation through) into physical models.
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Proton exchange membrane fuel cell degradation prediction based on Adaptive Neuro-Fuzzy Inference Systems .

Rosa Elvira Silva, +11 more
- 15 Jul 2014 - 
TL;DR: Validation results suggest that the proposed technique is well adapted to predict degradation in fuel cell systems.