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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.





Latest publications of team

Condition Monitoring of a Friction Drive System

Diego Jair Rodriguez Obando, John Jairo Martinez Molina, Christophe Bérenguer. Condition Monitoring of a Friction Drive System. 3rd IEEE Colombian Conference on Automatic Control, Oct 2017, Cartagena de Indias, Colombia. 〈hal-01628575〉

Détection de cibles spatialement structurées sous contrôle global d'erreur

Raphael Bacher, Florent Chatelain, Olivier Michel. Détection de cibles spatialement structurées sous contrôle global d'erreur. GRETSI 2017, Sep 2017, Juan les Pins, France. 〈hal-01563996〉

Méthode de σ-clipping par point fixe pour l'estimation de la distribution sous H0 dans le cadre de tests multiplesActes du GRETSI 2017

Céline Meillier, Raphael Bacher, Florent Chatelain, Olivier Michel. Méthode de σ-clipping par point fixe pour l'estimation de la distribution sous H0 dans le cadre de tests multiples. GRETSI 2017, Sep 2017, Juan les Pins, France. 〈hal-01563994〉


All publications of team
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