Structural damage identification has received considerable attention during the past
decades. Although several reviews have been presented, some new developments have …

The unscented Kalman filter (UKF) has proven to be an effective approach for the
identification of nonlinear systems from limited output measurements. However, the …

This paper presents a novel approach to substantially improve the detection accuracy of
structural damage via a one-dimensional convolutional neural network (1-D CNN) and a …

New optimization algorithms have been increasingly developed in the course of the recent
years. The accuracy of identified results in optimization‐based damage detection methods …

The extended Kalman filter (EKF) is an efficient tool for structural health monitoring and
vibration control due to its superiority. However, the conventional EKF approach is only …

Direct application of the Kalman filter algorithm to state estimation of civil structures presents
a computational challenge due to their high dimensions and complexity. Rewriting dynamic …

This article presents a probabilistic structural identification of the Tamar bridge using a
detailed finite element model. Parameters of the bridge cables initial strain and bearings …

In this paper, a stable and robust filter is proposed for structural identification. This filter
resolves the instability problems of the traditional extended Kalman filter (EKF). Instead of ad …

It is necessary to investigate the identification of structural systems and unknown inputs
under non‐Gaussian measurement noises. In recent years, a few scholars have proposed …

Steel cables serve as the key structural components in long-span bridges, and the force
state of the steel cable is deemed to be one of the most important determinant factors …