The present work offers a comprehensive overview of methods related to condition
assessment of bridges through Structural Health Monitoring (SHM) procedures, with a …

This paper presents a rapid machine learning-based damage detection framework for
identifying the damage extent of concrete shear wall buildings. For this purpose, a …

Damage diagnosis based on global structural vibrations critically depends on the sensor
layout, in particular when a small number of sensors is used for large structures under …

Progress in the field of Structural Health Monitoring (SHM) includes applications of model
data approaches with numerically generated responses originating from Finite Element (FE) …

Unsupervised techniques have gained much attention in the last decade as the most
practical real-time structural health monitoring (SHM) approach. However, there are still …

Damage localization based on ambient vibration data in combination with finite element
models can be challenging, in particular due to the large number of parameters in the model …

In seismic structural health monitoring (SHM), a structure is normally instrumented with
limited sensors at certain locations to monitor its structural behavior during an earthquake …

Abstract Model order selection is a fundamental task in subspace identification for estimation
of modal parameters, uncertainty propagation and damage diagnosis. However, the true …

This paper develops a model-assisted approach for determining predictive probability of
detection curves. The approach is “model-assisted,” as the damage-sensitive features are …

Subspace-based damage detection methods are widely used for civil engineering structures
modeled as linear time-invariant systems. For operating wind turbines modeled as linear …