Projecten per jaar
Vingerafdruk
Verdiep u in de onderzoeksgebieden waarop Faras Jamil actief is. Deze onderwerplabels komen uit het werk van deze persoon. Samen vormen ze een unieke vingerafdruk.
- 1 Soortgelijke profielen
Samenwerkingen en hoofdonderzoeksgebieden uit de afgelopen vijf jaar
Recente externe samenwerking op landen-/regioniveau. Duik in de details door op de stippen te klikken of
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FWOSB143: Foutdetectie en degradatietrends met behulp van hybride intelligentietechnieken en transfer learning met meerdere databronnen
Helsen, J., Nowe, A. & Jamil, F.
1/11/22 → 31/10/26
Project: Fundamenteel
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OZR3820: OZR-opvangmandaat: Multi-Machine Fout Detectie voor Wind Turbines gebruikmakend van Deep Transfer Learning
1/11/21 → 31/10/22
Project: Fundamenteel
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Farm-wide dynamic drivetrain event and diagnosis tracking using multi-modal data
Kestel, K., Chesterman, X., Jamil, F., Matthys, J. J., Vratsinis, K., Sterckx, J., Peeters, C. & Helsen, J., dec. 2025, Farm-wide dynamic drivetrain event and diagnosis tracking using multi-modal data. 1 redactie Springer Nature, Vol. 89. blz. 1-16 16 blz. (Forschung im Ingenieurwesen/Engineering Research).Onderzoeksoutput: Conference paper
Open Access -
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 blz., 012009.Onderzoeksoutput: Article › peer review
Open Access -
Wind turbine drivetrain health monitoring using physics informed deep learning.
Jamil, F., Peeters, C. & Helsen, J., 14 okt. 2024.Onderzoeksoutput: Poster
Bestand9 Downloads (Pure) -
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, blz. 663-668 6 blz.Onderzoeksoutput: 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 blz. 101689. (Proceedings of the ASME Turbo Expo; vol. 14).Onderzoeksoutput: Conference paper
1 Citaat (Scopus)
Activiteiten
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Automated condition monitoring using spectral autoencoders for fault detection in mechanical systems.
Faras Jamil (Speaker), Cédric Peeters (Contributor) & Jan Helsen (Contributor)
18 feb. 2025Activiteit: Talk or presentation at a conference
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DTU Wind And Energy Systems, Technical University of Denmark, Roskilde, Denmark research stay
Faras Jamil (Participant)
1 feb. 2025 → 30 apr. 2025Activiteit: Research and Teaching at External Organisation
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Wind turbine drivetrain fault detection using physics-informed multivariate deep learning
Faras Jamil (Speaker)
12 jul. 2023Activiteit: Talk or presentation at a conference
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A Hybrid Method for Fault Detection of Wind Turbine Drivetrains Using Machine Learning and Signal processing.
Faras Jamil (Speaker)
25 mei 2023Activiteit: 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 okt. 2026Activiteit: Written proposal