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Found 6 papers, 1 papers with code
Anomaly Detection in Offshore Wind Turbine Structures using Hierarchical Bayesian Modelling
Population-based structural health monitoring (PBSHM), aims to share information between members of a population.
On the hierarchical Bayesian modelling of frequency response functions
In this paper, a combined probabilistic FRF model is developed for a small population of nominally-identical helicopter blades, using a hierarchical Bayesian structure, to support information transfer in the context of sparse data.
Better Together: Using Multi-task Learning to Improve Feature Selection within Structural Datasets
There have been recent efforts to move to population-based structural health monitoring (PBSHM) systems.
Hierarchical Bayesian Modelling for Knowledge Transfer Across Engineering Fleets via Multitask Learning
Utilising an interpretable hierarchical Bayesian approach and operational fleet data, domain expertise is naturally encoded (and appropriately shared) between different sub-groups, representing (i) use-type, (ii) component, or (iii) operating condition.
Bayesian Modelling of Multivalued Power Curves from an Operational Wind Farm
Power curves capture the relationship between wind speed and output power for a specific wind turbine.
On risk-based active learning for structural health monitoring
A primary motivation for the development and implementation of structural health monitoring systems, is the prospect of gaining the ability to make informed decisions regarding the operation and maintenance of structures and infrastructure.
