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Sensor Networks in Structural Health Monitoring: From Theory to Practice

The intense development of novel data-driven and hybrid methods for structural health monitoring (SHM) has been demonstrated by field deployments on large-scale systems, including transport, wind energy, and building infrastructure. The actionability of SHM as an essential resource for life-cycle an...

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Збережено в:
Формат: Online
Мова:Англійська
Опубліковано: MDPI - Multidisciplinary Digital Publishing Institute 2022
Предмети:
probabilistic data-interpretation
Bayesian model updating
error-domain model falsification
iterative asset-management
practical applicability
computation time
swarm-based parallel control (SPC)
Internet of Things (IoT)
soil–structure interaction (SSI)
semi-active control
adjacent buildings
Bayesian inference
model updating
modal identification
structural dynamics
bridges
sensor placement optimisation
structural health monitoring
damage identification
mutual information
evolutionary optimisation
inertial sensor fusion
instrumented particle
MEMS
sediment entrainment
sensor calibration
frequency of entrainment
varying environmental and operational conditions
damage detection and localization
Gaussian process regression
autoregressive with exogenous inputs
distributed sensor network
mode shape curvatures
n/a
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues
Онлайн доступ:ONIX_20220111_9783036506326_13
Теги: Додати тег
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