Structural health monitoring (SHM) is the main contributor of the future's smart city to deal
with the need for safety, lower maintenance costs, and reliable condition assessment of …

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

The input-parameter-state estimation capabilities of a novel unscented Kalman filter is
examined herein on both linear and nonlinear systems. The unknown input is estimated in …

In recent years, a new research direction in structural condition assessment has been
focusing on developing automated or semi-automated procedures to identify a structure's …

Bridge infrastructure assets possess ultimate value for safe, resilient, and sustainable
transportation networks. Monitoring of bridge structural characteristics is an essential …

The response‐only model class selection capability of a novel deep convolutional neural
network method is examined herein in a simple, yet effective, manner. Specifically, the …

In several countries, infrastructure is in poor condition, and this situation is bound to remain
prevalent for the years to come. A promising solution for mitigating the risks posed by ageing …

The estimation of the dynamic states, the parameters, and the input of systems subjected to
wind loading is examined herein using a sequential Kalman filter. The procedure considers …

This paper presents a benchmark problem for the structural health monitoring community to
study tall buildings. The benchmark building is called the Green Building located at the …

Bayesian dynamic linear models (BDLMs) are traditionally used in the fields of applied
statistics and machine learning. This paper performs an empirical validation of BDLMs in the …