Recent progress on reliability analysis of offshore wind turbine support structures considering digital twin solutions

M Wang, C Wang, A Hnydiuk-Stefan, S Feng, I Atilla… - Ocean …, 2021 - Elsevier
Global wind energy has developed rapidly in recent years, and the offshore wind turbines
(OWTs) have been applied to much more applications. Because the support structure of an …

Unsupervised learning methods for data-driven vibration-based structural health monitoring: a review

K Eltouny, M Gomaa, X Liang - Sensors, 2023 - mdpi.com
Structural damage detection using unsupervised learning methods has been a trending
topic in the structural health monitoring (SHM) research community during the past decades …

Probabilistic physics of failure-based framework for fatigue life prediction of aircraft gas turbine discs under uncertainty

SP Zhu, HZ Huang, W Peng, HK Wang… - Reliability Engineering & …, 2016 - Elsevier
A probabilistic Physics of Failure-based framework for fatigue life prediction of aircraft gas
turbine discs operating under uncertainty is developed. The framework incorporates the …

Digital twin approach for damage-tolerant mission planning under uncertainty

PM Karve, Y Guo, B Kapusuzoglu, S Mahadevan… - Engineering Fracture …, 2020 - Elsevier
The digital twin paradigm that integrates the information obtained from sensor data, physics
models, as well as operational and inspection/maintenance/repair history of a system (or a …

Machine learning based prediction of piezoelectric energy harvesting from wake galloping

C Zhang, G Hu, D Yurchenko, P Lin, S Gu… - … Systems and Signal …, 2021 - Elsevier
Wake galloping is a phenomenon of aerodynamic instability and has vast potential in energy
harvesting. This paper investigates the vibration response of wake galloping piezoelectric …

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 …

A probabilistic Bayesian recurrent neural network for remaining useful life prognostics considering epistemic and aleatory uncertainties

J Caceres, D Gonzalez, T Zhou… - Structural Control and …, 2021 - Wiley Online Library
Deep learning‐based approach has emerged as a promising solution to handle big
machinery data from multi‐sensor suites in complex physical assets and predict their …

A local digital twin approach for identifying, locating and sizing cracks in CHS X-joints subjected to brace axial loading

EWW Cheok, X Qian, C Chen, ST Quek, MBI Si - Engineering Structures, 2024 - Elsevier
This paper aims to introduce a strain-interfaced local digital twin solution for a welded
circular hollow section (CHS) X-joint subjected to brace axial loading. The solution …

A hybrid optimization algorithm with Bayesian inference for probabilistic model updating

H Sun, R Betti - Computer‐Aided Civil and Infrastructure …, 2015 - Wiley Online Library
A hybrid optimization methodology is presented for the probabilistic finite element model
updating of structural systems. The model updating process is formulated as an inverse …

Time‐varying system identification using variational mode decomposition

P Ni, J Li, H Hao, Y Xia, X Wang… - Structural Control and …, 2018 - Wiley Online Library
A new time‐varying system identification approach is proposed in this paper by using
variational mode decomposition. The newly developed variational mode decomposition …