A deep neural network based model for a kind of magnetorheological dampers

Carlos A. Duchanoy, Marco A. Moreno-Armendáriz, Juan C. Moreno-Torres, Carlos A. Cruz-Villar

Producción científica: Contribución a una revistaArtículorevisión exhaustiva

22 Citas (Scopus)

Resumen

In this paper, a deep neural network based model for a set of small-scale magnetorheological dampers (MRD) is developed where relevant parameters that have a physical meaning are inputs to the model. An experimental platform and a 3D-printing rapid prototyping facility provided a set of different conditions including MRD filled with two different MR fluids, which were used to train a Deep Neural Network (DNN), which is the core of the proposed model. Testing results indicate the model could forecast the hysteretic response of magnetorheological dampers for different load conditions and various physical configurations.

Idioma originalInglés
Número de artículo1333
PublicaciónSensors (Switzerland)
Volumen19
N.º6
DOI
EstadoPublicada - 2 mar. 2019

Huella

Profundice en los temas de investigación de 'A deep neural network based model for a kind of magnetorheological dampers'. En conjunto forman una huella única.

Citar esto