State-of-the-art review on advancements of data mining in structural health monitoring

M Gordan, SR Sabbagh-Yazdi, Z Ismail, K Ghaedi… - Measurement, 2022 - Elsevier
To date, data mining (DM) techniques, ie artificial intelligence, machine learning, and
statistical methods have been utilized in a remarkable number of structural health monitoring …

Recent advancement of concrete dam health monitoring technology: A systematic literature review

G Prakash, R Dugalam, M Barbosh, A Sadhu - Structures, 2022 - Elsevier
The health monitoring of dams has become a topic of paramount importance to maintain the
sustainability and resiliency of our society. The dam health monitoring (DHM) models …

Bayesian dynamic regression for reconstructing missing data in structural health monitoring

YM Zhang, H Wang, Y Bai, JX Mao… - Structural Health …, 2022 - journals.sagepub.com
Massive data that provide valuable information regarding the structural behavior are
continuously collected by the structural health monitoring (SHM) system. The quality of …

Sparse Gaussian process regression for multi-step ahead forecasting of wind gusts combining numerical weather predictions and on-site measurements

H Wang, YM Zhang, JX Mao - Journal of Wind Engineering and Industrial …, 2022 - Elsevier
Accurate forecasts of wind gusts are crucially important for wind power generation, severe
weather warnings, and the regulation of vehicle speed. To improve the short-term and long …

Bayesian multiple linear regression and new modeling paradigm for structural deflection robust to data time lag and abnormal signal

H Zhao, Y Ding, L Meng, Z Qin, F Yang… - IEEE Sensors …, 2023 - ieeexplore.ieee.org
Long-span bridges are the lifeline throats of urban transportation network. Deflection (ie,
deformation) behavior of long-span bridges is complex. It can be found from long-term …

[HTML][HTML] Abnormal data detection for structural health monitoring: State-of-the-art review

Y Deng, Y Zhao, H Ju, TH Yi, A Li - Developments in the Built Environment, 2024 - Elsevier
Structural health monitoring (SHM) is widely used to monitor and assess the condition and
performance of engineering structures such as, buildings, bridges, dams, and tunnels …

Machine learning-assisted improved anomaly detection for structural health monitoring

S Samudra, M Barbosh, A Sadhu - Sensors, 2023 - mdpi.com
The importance of civil engineering infrastructure in modern societies has increased lately
due to the growth of the global economy. It forges global supply chains facilitating enormous …

Uncertainty‐aware convolutional neural network for explainable artificial intelligence‐assisted disaster damage assessment

CS Cheng, AH Behzadan… - Structural Control and …, 2022 - Wiley Online Library
Accurate damage assessment is a critical step in post‐disaster risk assessment, mitigation,
and recovery. Current practices performed by experts and reconnaissance teams in the form …

A general data quality evaluation framework for dynamic response monitoring of long-span bridges

Y Deng, H Ju, G Zhong, A Li, Y Ding - Mechanical Systems and Signal …, 2023 - Elsevier
The structural health monitoring system (SHM) of long-span bridges inevitably produces low-
quality data. It is important to evaluate the data quality and screen out normal data. Most …

Monitoring-based analysis of wind-induced vibrations of ultra-long stay cables during an exceptional wind event

H Zhang, H Wang, Z Xu, Y Zhang, T Tao… - Journal of Wind …, 2022 - Elsevier
Ultra-long stay cables characterized as high flexibility are prone to large-amplitude
vibrations. Much attention has been paid to the vibrations of stay cables under normal wind …