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Dive into the research topics where Faras Jamil is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
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Collaborations and top research areas from the last five years
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FWOSB143: Fault detection and degradation trending using hybrid intelligence techniques and multi-source transfer learning
Helsen, J., Nowe, A. & Jamil, F.
1/11/22 → 31/10/26
Project: Fundamental
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OZR3820: Backup mandate Research Council: Multi-Machine Fault Detection for Wind Turbines using Deep Transfer Learning.
1/11/21 → 31/10/22
Project: Fundamental
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Offshore field experimentation for novel hybrid condition monitoring approaches
Kestel, K., Jamil, F., Matthys, J. J., Vratsinis, K., Sterckx, J., Marini, R., Peeters, C. & Helsen, J., Apr 2024, In: Journal of Physics: Conference Series. 2745, 1, 12 p., 012009.Research output: Contribution to journal › Article › peer-review
Open Access -
Signal processing informed deep learning for failure detection in a fleet of multi-stage planetary gearboxes with limited knowledge about characteristic frequencies
Helsen, J., Perez Sanjines, F. R., Jamil, F., Antoni, J. & Peeters, C., 2023, AIAC 2023: 20th Australian International Aerospace Congress: 20th Australian International Aerospace Congress. Melbourne: Engineers Australia, p. 663-668 6 p.Research output: Chapter in Book/Report/Conference proceeding › Conference paper
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Wind Turbine Drivetrain Fault Detection Using Multi-Variate Deep Learning Combined With Signal Processing
Jamil, F., Avila, F. J., Vratsinis, K., Peeters, C. & Helsen, J., 26 Jun 2023, Volume 14: Wind Energy. ASME, 7 p. 101689. (Proceedings of the ASME Turbo Expo; vol. 14).Research output: Chapter in Book/Report/Conference proceeding › Conference paper
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Wind turbine drivetrain fault detection using physics-informed multivariate deep learning
Jamil, F., Peeters, C., Verstraeten, T. & Helsen, J., 19 Jul 2023, Surveillance, Vibrations, Shock and Noise. HAL open science, 9 p.Research output: Chapter in Book/Report/Conference proceeding › Conference paper
Open Access -
A deep boosted transfer learning method for wind turbine gearbox fault detection
Jamil, F., Verstraeten, T., Nowé, A., Peeters, C. & Helsen, J., Sep 2022, In: Renewable Energy. 197, p. 331-341 11 p.Research output: Contribution to journal › Article › peer-review
45 Citations (Scopus)55 Downloads (Pure)
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A Hybrid Method for Fault Detection of Wind Turbine Drivetrains Using Machine Learning and Signal processing.
Faras Jamil (Speaker)
25 May 2023Activity: Talk or presentation › Talk or presentation at a conference
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Wind turbine drivetrain fault detection using physics-informed multivariate deep learning
Faras Jamil (Speaker)
12 Jul 2023Activity: Talk or presentation › Talk or presentation at a conference
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Fault detection and degradation trending using hybrid intelligence techniques and multi-source transfer learning
Faras Jamil (Recipient), Jan Helsen (Supervisor), Cédric Peeters (Supervisor), Timothy Verstraeten (Supervisor) & Ann Nowe (Supervisor)
1 Nov 2022 → 31 Oct 2026Activity: Other › Written proposal