The current development of structural health monitoring for bridges: a review

Z Deng, M Huang, N Wan, J Zhang - Buildings, 2023 - mdpi.com
The health monitoring system of a bridge is an important guarantee for the safe operation of
the bridge and has always been a research hotspot in the field of civil engineering. This …

Recent advances in uncertainty quantification in structural response characterization and system identification

K Zhou, Z Wang, Q Gao, S Yuan, J Tang - Probabilistic Engineering …, 2023 - Elsevier
Structural dynamics has numerous practical applications, such as structural analysis,
vibration control, energy harvesting, system identification, structural safety assessment, and …

Towards probabilistic data‐driven damage detection in SHM using sparse Bayesian learning scheme

QA Wang, Y Dai, ZG Ma, YQ Ni, JQ Tang… - … Control and Health …, 2022 - Wiley Online Library
Despite continuous evolution and development of structural health monitoring (SHM)
technology, interpreting a huge amount of sensed data from a sophisticated SHM system to …

Real-time Bayesian damage identification enabled by sparse PCE-Kriging meta-modelling for continuous SHM of large-scale civil engineering structures

E García-Macías, F Ubertini - Journal of Building Engineering, 2022 - Elsevier
This work presents a surrogate model-based Bayesian model updating (BMU) approach for
automated damage identification of large-scale structures, which outperforms methods …

Efficient Laplace prior-based sparse Bayesian learning for structural damage identification and uncertainty quantification

D Xie, ZR Lu, G Li, J Liu, L Wang - Mechanical Systems and Signal …, 2023 - Elsevier
Assessing the damage state from the measurement data is central to structural health
monitoring. Due to the ubiquitous existence of uncertainty factors in structural model and …

Sparse Bayesian technique for load identification and full response reconstruction

Y Li, X Wang, Y Xia, L Sun - Journal of Sound and Vibration, 2023 - Elsevier
Most load identification methods require that the load location is known in advance. A
sparse Bayesian framework is proposed in this study to identify the force location and time …

Physics-guided generative adversarial network for probabilistic structural system identification

Y Yu, Y Liu - Expert Systems with Applications, 2024 - Elsevier
Structural system identification (ID) is an important tool for many structural and infrastructure
applications, such as structural health monitoring and structural model updating. A novel …

An anomaly pattern detection for bridge structural response considering time-varying temperature coefficients

Y Ren, Q Ye, X Xu, Q Huang, Z Fan, C Li, W Chang - Structures, 2022 - Elsevier
To improve the detection rate in the bridge anomaly detection, this study proposes an
anomaly pattern detection method based on the time-varying temperature–displacement …

A Markov chain Monte Carlo-based Bayesian framework for system identification and uncertainty estimation of full-scale structures

ZY Liu, JH Yang, HF Lam, LX Peng - Engineering Structures, 2023 - Elsevier
Identifying modal parameters and updating finite element models (FEMs) of real structures
through ambient tests is essential in Structural Health Monitoring (SHM). However, efficiently …

Efficient structural model updating with spatially sparse modal data: A Bayesian perspective

Q Dollon - Mechanical Systems and Signal Processing, 2023 - Elsevier
Structural model updating was born from the need to adjust advanced finite element models
to match with the observations of the real asset. An important branch of the discipline is …