A Novel Generic Diagnosis Algorithm in the Time Domain Representation

Etienne Dijoux, Cédric Damour, Michel Benne () and Alexandre Aubier
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Etienne Dijoux: ENERGY Lab—LE2P, University La Reunion, 97415 Saint-Denis, France
Cédric Damour: ENERGY Lab—LE2P, University La Reunion, 97415 Saint-Denis, France
Michel Benne: ENERGY Lab—LE2P, University La Reunion, 97415 Saint-Denis, France
Alexandre Aubier: Vehicle and Hydrogen Innovation, Crea + Parts Company, 97438 Sainte-Marie, France

Energies, 2022, vol. 16, issue 1, 1-18

Abstract: The health monitoring of a system remains a major issue for its lifetime preservation. In this paper, a novel fault diagnosis algorithm is proposed. The proposed diagnosis approach is based on a unique variable measurement in the time domain and manages to extract the system behavior evolution. The developed tool aims to be generic to several physical systems with low or high dynamic behavior. The algorithm is depicted in the present paper and two different applications are considered. The performance of the novel proposed approach is experimentally evaluated on a fan considering two different faulty conditions and on a proton exchange membrane fuel cell. The experimental results demonstrated the high efficiency of the proposed diagnosis tool. Indeed, the algorithm can discriminate the two faulty operation modes of the fan from a normal condition and also manages to identify the current system state of health. Regarding the fuel cell state of health, only two conditions are tested and the algorithm is able to detect the fault occurrence from a normal operating mode. Moreover, the very low computational cost of the proposed diagnosis tool makes it especially suitable to be implemented on a microcontroller.

Keywords: fan fault operation mode; proton exchange membrane fuel cell; time-domain diagnosis; fault detection and identification (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
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