All Outputs (4)

Multi Point Sensing and Defect Detection of Wind Turbine Blades: An Approach Using Fibre Bragg Gratings (2025)
Thesis
Sihivahana Sarma, A. (2025). Multi Point Sensing and Defect Detection of Wind Turbine Blades: An Approach Using Fibre Bragg Gratings. (Thesis). University of Hull. https://hull-repository.worktribe.com/output/5126324

Structural Health Monitoring (SHM) of Wind Turbine Blades (WTBs) plays a critical role in ensuring safe and cost-effective operations of these complex structures. However, detecting manufacturing-induced defects and operation-induced damages poses si... Read More about Multi Point Sensing and Defect Detection of Wind Turbine Blades: An Approach Using Fibre Bragg Gratings.

Energy Maximization of Control for a Point Absorber Wave Energy Converter (2024)
Thesis
Li, D. Energy Maximization of Control for a Point Absorber Wave Energy Converter. (Thesis). University of Hull. https://hull-repository.worktribe.com/output/4704554

To date, one of the main challenges and requirements in wave energy technologies is to design energy-maximising control for a wave energy converter (WEC) device to achieve the energy maximization production, so as to reduce the levelized cost of ener... Read More about Energy Maximization of Control for a Point Absorber Wave Energy Converter.

Fault-tolerant load reduction control for large offshore wind turbines (2019)
Thesis
Liu, Y. Fault-tolerant load reduction control for large offshore wind turbines. (Thesis). University of Hull. https://hull-repository.worktribe.com/output/4270015

Offshore wind turbines suffer from asymmetrical loading (blades, tower etc.), leading to enhanced structural fatigue. As well as asymmetrical loading different types of faults (pitch system faults etc.) can occur simultaneously, causing degradation o... Read More about Fault-tolerant load reduction control for large offshore wind turbines.

Direct Speech Reconstruction from Articulatory Sensor Data by Machine Learning (2017)
Journal Article
Gonzalez, J. A., Cheah, L. A., Gomez, A. M., Green, P. D., Gilbert, J. M., Ell, S. R., Moore, R. K., & Holdsworth, E. (2017). Direct Speech Reconstruction from Articulatory Sensor Data by Machine Learning. IEEE/ACM transactions on audio, speech, and language processing, 25(12), 2362-2374. https://doi.org/10.1109/TASLP.2017.2757263

© 2014 IEEE. This paper describes a technique that generates speech acoustics from articulator movements. Our motivation is to help people who can no longer speak following laryngectomy, a procedure that is carried out tens of thousands of times per... Read More about Direct Speech Reconstruction from Articulatory Sensor Data by Machine Learning.