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Communication Dans Un Congrès Année : 2019

Data Driven Methods for the Prediction of Failures

Résumé

The reliability and safety operation of an industrial system are the main objectives of industrial companies to remain competitive in a constantly growing market. Unexpected shutdowns can often lead to physical hazards as well as economic consequences in key sectors. Hence, fault prediction emerges as an important focus of the industry. Thus, this paper aims to detail the prognostic aspect and provides a state of the art of existing data-driven prognostic methods used in the literature. This paper shows the diversity of possible prognostic methods and the choice of one among them that will define a framework for industrials.
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Dates et versions

hal-02469105 , version 1 (06-02-2020)

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Abdenour Soualhi, Hubert Razik, Guy Clerc. Data Driven Methods for the Prediction of Failures. 12th IEEE SDEMPED, Aug 2019, Toulouse, France. pp.474-480, ⟨10.1109/DEMPED.2019.8864877⟩. ⟨hal-02469105⟩
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