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 …
(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
Structural damage detection using unsupervised learning methods has been a trending
topic in the structural health monitoring (SHM) research community during the past decades …
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
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 …
turbine discs operating under uncertainty is developed. The framework incorporates the …
Digital twin approach for damage-tolerant mission planning under uncertainty
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 …
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
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 …
harvesting. This paper investigates the vibration response of wake galloping piezoelectric …
Towards probabilistic data‐driven damage detection in SHM using sparse Bayesian learning scheme
Despite continuous evolution and development of structural health monitoring (SHM)
technology, interpreting a huge amount of sensed data from a sophisticated SHM system to …
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 …
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
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 …
circular hollow section (CHS) X-joint subjected to brace axial loading. The solution …
A hybrid optimization algorithm with Bayesian inference for probabilistic model updating
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 …
updating of structural systems. The model updating process is formulated as an inverse …
Time‐varying system identification using variational mode decomposition
A new time‐varying system identification approach is proposed in this paper by using
variational mode decomposition. The newly developed variational mode decomposition …
variational mode decomposition. The newly developed variational mode decomposition …