A machine learning perspective on frictional contacts and self-excited vibrations.
Mael Thevenot  1, *, @  , Merten Stender  2, @  , Jean-François Brunel  3, @  , Charlotte Geier  2, @  , Philippe Dufrénoy  3, @  , Norbert Hoffmann  4, 2, @  
1 : Univ. Lille, CNRS, Centrale Lille, UMR 9013 - LaMcube - Laboratoire de Mécanique Multiphysique Multiéchelle, F-59000, Lille, France  (LaMcube)  -  Website
University of Lille, 59655 Villeneuve d'Ascq, France
Bâtiment ESPRIT, avenue Paul Langevin 59650 Villeneuve-d'Ascq -  France
2 : Hamburg University of Technology, Dynamics Group, Hamburg, Germany
Am Schwarzenberg-Campus 1, 21073 Hamburg, Allemagne -  Germany
3 : Univ. Lille, CNRS, Centrale Lille, UMR 9013 - LaMcube - Laboratoire de Mécanique Multiphysique Multiéchelle, F-59000, Lille, France
University of Lille, 59655 Villeneuve d'Ascq - France
Av. Paul Langevin, 59650 Villeneuve-d'Ascq -  France
4 : Imperial College London, Department of Mechanical Engineering, London, United Kingdom
58 Princes Gate, South Kensington, London SW7 1AY, Royaume-Uni -  United Kingdom
* : Corresponding author
Subject : : Oral + Young Scientist Award
Topics : MS-09 Nonlinear Dynamics in Engineering Systems
Keywords : Friction ; induced vibrations ; Data science ; Virtual twin ; Third body approach ; Thermomechanical characterisation
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