Advanced data analysis using machine learning tools and deep network architectures

Research proposals

  • Research area

    Operations and remote autonomous monitoring

  • Institution

    University of Sheffield

  • Research project

    Advanced data analysis using machine learning tools and deep network architectures

  • Lead supervisor

    Dr Nikolaos Dervilis (Senior Lecturer – Department of Mechanical Engineering, University of Sheffield)

  • Supervisory Team

    Dr Nikolaos Dervilis (Senior Lecturer – Department of Mechanical Engineering, University of Sheffield)
    Prof Keith Worden (Mechanical Engineering, University of Sheffield)

Project Description:

As offshore wind turbines are entering a new technological era; more sensing systems are adopted which results to a geometrical increase of high sampling data. This project aims to promptly process the massive collection of data and automatically provide advanced data features that are rich in information. Artificial Intelligence tools like deep learning architectures shall be investigated spanning from deep neural networks to Bayesian deep networks like Gaussians Processes (GPs). The aim is to provide online, fast and sparse processing of huge amounts of data in order to deliver intelligent data understanding across wind turbine fleets and farms (e.g. informative structural health diagnosis systems (SHM)) under various operating and environmental conditions.

Download all research proposals here