Influence of smart sensors on structural health monitoring systems and future asset management practices
Recent developments in networked and smart sensors have significantly changed the way
Structural Health Monitoring (SHM) and asset management are being carried out. Since the …
Structural Health Monitoring (SHM) and asset management are being carried out. Since the …
[HTML][HTML] A digital twin framework for civil engineering structures
The digital twin concept represents an appealing opportunity to advance condition-based
and predictive maintenance paradigms for civil engineering systems, thus allowing reduced …
and predictive maintenance paradigms for civil engineering systems, thus allowing reduced …
A review of physics-based learning for system health management
The monitoring process for complex infrastructure requires collecting various data sources
with varying time scales, resolutions, and levels of abstraction. These data sources include …
with varying time scales, resolutions, and levels of abstraction. These data sources include …
SHM under varying environmental conditions: An approach based on model order reduction and deep learning
Data-driven approaches to structural health monitoring (SHM) have been recently shown to
be a powerful paradigm, helping to lead to an evolution of traditional scheduled-based …
be a powerful paradigm, helping to lead to an evolution of traditional scheduled-based …
Structural health monitoring of civil structures: A diagnostic framework powered by deep metric learning
Recent advances in learning systems and sensor technology have enabled powerful
strategies for autonomous data-driven damage detection in structural systems. This work …
strategies for autonomous data-driven damage detection in structural systems. This work …
An educational review on distributed optic fiber sensing based on Rayleigh backscattering for damage tracking and structural health monitoring
L Chamoin, S Farahbakhsh… - … Science and Technology, 2022 - iopscience.iop.org
This paper is a review on distributed optic fiber sensing for structural health monitoring
applications, with a deeper focus on technologies relying on the Rayleigh backscattering …
applications, with a deeper focus on technologies relying on the Rayleigh backscattering …
Multi-storey shear type buildings under earthquake loading: Adversarial learning-based prediction of the transient dynamics and damage classification
In this paper, the transient dynamic response of shear type multi-storey buildings subjected
to earthquake ground motion is generated via adversarial learning technique under different …
to earthquake ground motion is generated via adversarial learning technique under different …
[HTML][HTML] A multi-fidelity surrogate model for structural health monitoring exploiting model order reduction and artificial neural networks
Stochastic approaches to structural health monitoring (SHM) are often inevitably limited by
computational constraints. For instance, for Markov chain Monte Carlo algorithms relying …
computational constraints. For instance, for Markov chain Monte Carlo algorithms relying …
Model error effects in supervised damage identification of structures with numerically trained classifiers
P Seventekidis, D Giagopoulos - Mechanical Systems and Signal …, 2023 - Elsevier
Progress in the field of Structural Health Monitoring (SHM) includes applications of model
data approaches with numerically generated responses originating from Finite Element (FE) …
data approaches with numerically generated responses originating from Finite Element (FE) …
Deep learning for structural health monitoring: Data, algorithms, applications, challenges, and trends
J Jia, Y Li - Sensors, 2023 - mdpi.com
Environmental effects may lead to cracking, stiffness loss, brace damage, and other
damages in bridges, frame structures, buildings, etc. Structural Health Monitoring (SHM) …
damages in bridges, frame structures, buildings, etc. Structural Health Monitoring (SHM) …