| A deep boosted transfer learning method for wind turbine gearbox fault detection F Jamil, T Verstraeten, A Nowé, C Peeters, J Helsen Renewable Energy 197, 331-341, 2022 | 39 | 2022 |
| Wind turbine drivetrain fault detection using physics-informed multivariate deep learning F Jamil, C Peeters, T Verstraeten, J Helsen Surveillance, Vibrations, Shock and Noise, 2023 | 1 | 2023 |
| Wind turbine drivetrain fault detection using multi-variate deep learning combined with signal processing F Jamil, F Jara Avila, K Vratsinis, C Peeters, J Helsen Turbo Expo: Power for Land, Sea, and Air 87127, V014T37A003, 2023 | 1 | 2023 |
| Signal processing informed deep learning for failure detection in a fleet of multi-stage planetary gearboxes with limited knowledge about characteristic frequencies J Helsen, F Perez, F Jamil, J Antoni, C Peeters AIAC 2023: 20th Australian International Aerospace Congress: 20th Australian …, 2023 | 1 | 2023 |
| Offshore field experimentation for novel hybrid condition monitoring approaches K Kestel, F Jamil, JJ Matthys, K Vratsinis, J Sterckx, R Marini, C Peeters, ... Journal of Physics: Conference Series 2745 (1), 012009, 2024 | | 2024 |
| Hybrid signal processing and data-driven approaches for vibration-based condition monitoring of a fleet of wind turbine drivetrains C Peeters, K Kestel, PJ Daems, J Matthys, G Protopapadakis, ... | | |
