Voltage singularity classification for fuel cell diagnosis

The study summarized in this paper proposes a new tool for PEMFC non-intrusive diagnosis based on voltage singularity measurement and classification. The method takes advantage of the non-linearities associated with discontinuities introduced in the dynamic response data resulting from various failure modes. Continuous wavelets and multifractal formalism, named WTMM (Wavelet Transform Modulus Maxima), are used together to quantify the singularity strength of the signal. The singularities signature of poor PEMFC operating conditions (faults) is first revealed through multifractal spectra. Then, these ones are classified using SVM (Support Vector Machine). The good classification rates obtained demonstrate that the multifractal spectrum based on WTMM is effective to extract the incipient fault features during PEMFC operation. The proposed method leads to a promising non-intrusive and low cost diagnostic tool to achieve on-line characterizations of dynamical PEMFC behaviors.

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Additional Info

Field Value
Source EFCF 2013 - European Fuel Cell Conference
Author Benouioua, Djedjiga, Candusso, Denis, Harel, Fabien, Oukhellou, Latifa
Maintainer CCSD
Last Updated May 7, 2026, 19:23 (UTC)
Created May 7, 2026, 19:23 (UTC)
Identifier hal-00918936
Language en
contributor Laboratoire des Technologies Nouvelles (IFSTTAR/COSYS/LTN) ; Institut Français des Sciences et Technologies des Transports, de l'Aménagement et des Réseaux (IFSTTAR)
creator Benouioua, Djedjiga
date 2013-12-11T00:00:00
harvest_object_id 4d9950e2-2543-4fd2-aa0b-969fb22d8e8a
harvest_source_id 3374d638-d20b-4672-ba96-a23232d55657
harvest_source_title test moissonnage SELUNE
metadata_modified 2024-12-03T00:00:00
set_spec type:COMM