This doctoral course builds a unified framework linking linearsystems
theory, digital signal processing, and modern artificial intelligence
for structural engineering and structural health monitoring
(SHM). Across the lectures it introduces the core signalprocessing
algorithms — continuous- and discrete-time linear systems,
Fourier analysis, sampling theory, the z-transform, digital filtering,
and statistical, output-only modal identification.
These foundations are then carried into data-driven methods, progressing
from feature engineering and classical machine learning to
deep architectures (CNNs, recurrent and autoencoder models) and,
finally, to physics-informed and hybrid learning that fuses mechanistic
models with data-driven inference.
The unifying goal is the structural health monitoring of real systems:
detecting, localising, and interpreting damage directly from measured
response.
9, 10 Luglio 2026 15 Luglio 2026 16, 21, 22 Luglio 2026 15:00 – 18:00 10:00 – 13:30 15:00 – 18:00
Luogo
Aula Riunioni 329
Dipartimento di Ingegneria Strutturale e Geotecnica
Via Eudossiana 18, Roma