Tudore / BNNs-for-FOWT-Mooring-Fault-Detection

In this project, we study the potential applications of Bayesian networks for the identification of mooring line damage for floating offshore wind turbines.

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Bayesian Neural Networks for Floating Offshore Wind Turbine Mooring Fault Detection

In this project, we study the potential applications of Bayesian networks for the identification of mooring line damage for floating offshore wind turbines.

  • main.py is the main Python code we want to run to train a BNN.
  • The data directory contains the set of synthetic data used for training and validation of our model.
  • The prev directory contains previous work in the form of published/submitted papers, codes, etc.
  • The src directory contains all the modules required to run main.py, including preprocessing, architecture design, model implementation and training, and postprocessing.
  • The out directory contains figures, tables, and statistics obtained from the trained BNN.
  • The docs directory contains reference to various topics including Bayesian inference, Bayesian neural networks, uncertainty quantification, etc.

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In this project, we study the potential applications of Bayesian networks for the identification of mooring line damage for floating offshore wind turbines.


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