Characterization of the modal response using Deep recurrent neural networks

• Published in: Engineering structures Vol. 256; p. 113915
• Main Authors: González, Wladimir M., Ferrada, Andrés, Boroschek, Rubén L., López Droguett, Enrique
• Format: Journal Article
• Language: English
• Published: Kidlington Elsevier Ltd 01.04.2022; Elsevier BV
• Subjects: Civil engineering; Damage detection; Deep learning; Environmental effects; Frequency variation; Long short-term memory; Modal Response; Neural networks; Parameter sensitivity; Recurrent neural networks; Sensitivity; SHM; Structural health monitoring; Tracking; Urban areas; Deep learning; Modal Response; SHM; Neural networks; Environmental effects

•A building is monitored with a low density/low resolution sensor system.•Deep learning recurrent neural networks are used to predict the modal response.•Temperature and solar radiation based models are tested for the modal frequency.•LSTM and MLP layers are used in the neural network arquitecture....