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Conference Papers Year : 2022

Advanced machine learning for the detection of single event effects

Abstract

With the increase of component complexity, protection against single event effects becomes a critical point for the disponibility and reliability of space systems. In this paper, machine learning is investigated to improve the detection of radiation faults. An algorithm named DYD² that meets space application requirements is proposed. In addition, a study to improve the characterisation of single event effects through feature extraction is described. Finally, results of experimentation based on a heavy-ion campaign test are discussed.
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Dates and versions

hal-03789895 , version 1 (30-09-2022)

Identifiers

  • HAL Id : hal-03789895 , version 1

Cite

Adrien Dorise, Audine Subias, Louise Travé-Massuyès, Corinne Alonso. Advanced machine learning for the detection of single event effects. RADECS 2022, Oct 2022, Venice, Italy. ⟨hal-03789895⟩
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