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Research project

Multi-functional nonlinear tuned vibration energy harvester for intelligent rotating systems

  • Lead researcher:
  • Research funder:
    Royal Society
  • Status:
    Active

Project overview

Aviation industry has been increasingly transformed by integrating more automation and digital technologies in manufacturing and operations. For example, wireless Structural Health Monitoring (SHM) can be effectively achieved in aerospace systems through embedded sensor technologies. This provides a great opportunity to
improve the reliability and sustainability of critical rotating systems in many aerospace systems such as helicopter blades, fan blade systems. These rotating blades are often subjected to extremely complex dynamic loads during high speed flights that induce significant vibrations leading to high cycle fatigue problems with
major implication on the cost and safety. The wireless SHM can effectively help monitor in-service mechanical stress of rotating blades to optimise operational conditions and avoid catastrophic failures but also record manufacturing process for sustainable life cycle management. One of key industrial challenges is on the lack of sustainable power sources to substitute batteries for long-term wireless sensing. Fortunately, these rotating blades often have rich vibrational energy due to its high modal density. The idea of this project is to develop novel embedded multi-functional nonlinear tuned vibration energy harvesters for self-charging sensing through advanced nonlinear electrical and mechanical designs. It will make the embedded system capable of both vibration energy harvesting in a wide bandwidth frequency and adaptive vibration suppression. This project will effectively integrate advanced technologies from different research communities leading to novel embedded energy harvesters for rotating systems. It will forge a strong and long-term collaboration between two applicants and their teams and related experts across China and UK.

Staff

Lead researcher

Dr Jie Yuan FHEA, CEng, MRAeS

Lecturer

Research interests

  • Computational methods for complex dynamical systems
  • Dynamic control using novel functional material and interface
  • Non-deterministic approaches for robust optimisation and identification