In recent decades, structural health monitoring (SHM) has gained increased importance for
ensuring the sustainability and serviceability of large and complex structures. To design an …

Due to the damage of sensors or transmission equipment, abnormal monitoring data
inevitably exists in the measured raw data, and it significantly impacts the condition …

Despite continuous evolution and development of structural health monitoring (SHM)
technology, interpreting a huge amount of sensed data from a sophisticated SHM system to …

The quantification of uncertainty in civil structures poses a significant challenge in
contemporary research due to the substantial computational demands involved. This study …

The conventional model updating based on sensitivity analysis generally employs l 1-norm
regularizer to characterize the sparsity of the structural damage. However, the l 1-norm …

This study proposes an effective damage detection method for laminated composite
structures under the influence of nonstationary colored noise using condensed Frequency …

The emergence of the Internet of Things (IoT) has facilitated the development and usage of
low-computational microcontrollers at the edge of the network, which process data in the …

Deep learning (DL) techniques have been developed for structural damage detection by
training the network to dig damage-sensitive features from big data. However, most …

Damage detection of civil engineering structures needs to consider the effect of normal
environmental variations on structural dynamic properties. This study develops a novel …

Sparse Bayesian learning methods have been successfully applied to the community of
structural damage identification, which commonly assumes that the uncertainties from …