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Communication Dans Un Congrès Année : 2017

Fault diagnosis and prognosis by using input-output hidden Markov models applied to a diesel generator

Résumé

In this paper, a method to implement a platform of failure diagnosis and prognosis, and health monitoring based on data using Input Output Hidden Markov Models (IOHMM) is proposed. Several sensors on a diesel generator system give information such as on-line operating conditions. The goal of this work is to use on-line collected data in order to determine degradation state of the diesel generator system. Classification of data thanks to IOHMM allows the monitoring of the component health state and operates fault diagnosis and prognosis.
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Dates et versions

hal-01537742 , version 1 (12-06-2017)

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Timothée Klingelschmidt, Philippe Weber, Christophe Simon, Flavien Peysson, Didier Theilliol. Fault diagnosis and prognosis by using input-output hidden Markov models applied to a diesel generator. 25th Mediterranean Conference on Control and Automation, MED 2017, Jul 2017, Valletta, Malta. ⟨10.1109/MED.2017.7984302⟩. ⟨hal-01537742⟩
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