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Team

Signal automatique pour la surveillance, le diagnostic et la biomécanique
Team manager : Franck QUAINE, Pierre GRANJON

SAIGA team (Signal and Automatics for monitoring, diagnosis, and the Biomechanics) conducts research on the analysis and modelling of complex systems. The work focuses on understanding, monitoring, diagnosis and safety of industrial, natural and living biomechanical systems.

Key words: modeling, time-frequency, multi-sensor, pattern recognition, separation of sources, biomechanical models, EMG, human movement, surveillance, safety, diagnosis, prognosis

 

vignette slides SaigaTeam presentation :
Français (pdf, 119 ko)
English (pdf, 100 ko)

 

 

TOPICS of the team

Topic 1: models of signal processing for surveillance of systems

Topic 2: models for decision in surveillance and safety

Topic 3: models and signals for Biomechanics

Complex systems studied by SAIGA are the mechatronic systems, production systems, transportation or communication, and living systems. These systems are sometimes distributed. In some cases, methodologies must be autonomous and integrated, and therefore respect the constraints of embedded systems. The 3 topics of the team reflect its composition and reinforce its disciplinary coherence around signal, automatic and biomechanics. This composition is original and relies on the presence of skills in these disciplines within the team, which explains the originality of our results.

Preferred applications of SAIGA team are energy and health, fields that federate the core activity of every one on each topic.





Last publications of team

An ensemble of models for integrating dependent sources of information for the prognosis of the remaining useful life of Proton Exchange Membrane Fuel Cells

Dacheng Zhang, Piero Baraldi, Catherine Cadet, Nadia Yousfi-Steiner, Christophe Bérenguer, et al.. An ensemble of models for integrating dependent sources of information for the prognosis of the remaining useful life of Proton Exchange Membrane Fuel Cells. Mechanical Systems and Signal Processing, Elsevier, 2019, 124, pp.479-501. 〈https://authors.elsevier.com/a/1YYb739~t0RWPs〉. 〈10.1016/j.ymssp.2019.01.060〉. 〈hal-02014907〉

Design of a Low Complexity Interference Detector for LPWA Networks

Chhayarith Heng Uy, Carolynn Bernier, Sylvie Charbonnier. Design of a Low Complexity Interference Detector for LPWA Networks. IEEE I$^2$MTC 2019. IEEE International Instrumentation and Measurement Technology Conference, May 2019, Auckland, Australia. 〈cea-01972990〉

Uncertainty sensitivity assessment on the optimization of the design of complex energy systems: Two complementary approaches

Amélia Nadal, Alain Ruby, Cyril Bourasseau, Delphine Riu, Christophe Bérenguer. Uncertainty sensitivity assessment on the optimization of the design of complex energy systems: Two complementary approaches. International Renewable Energy Storage Conference (IRES 2019), Mar 2019, Düsseldorf, Germany. 〈hal-02072307〉


Voir toutes les publications de l'équipe dans HAL
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