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Helsen, Jan
ORCID
Informatie laatst gewijzigd: 2023-05-15

Instituut
Publicaties (38)

Vrije Universiteit Brussel; Faculteit Ingenieurswetenschappen; Vakgroep Toegepaste Mechanica (MECH), meer

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A1 publicaties (14) [show]
Vratsinis, K.; Marini, R.; Daems, P.; Pauscher, L.; van Beeck, J.; Helsen, J. (2026). Impact of inflow conditions and turbine placement on the performance of offshore wind turbines exceeding 7 MW. Wind Energy Science 11(5): 1803-1820. https://dx.doi.org/10.5194/wes-11-1803-2026, meer Ally, S.; Verstraeten, T.; Nowe, A.; Helsen, J. (2025). Day-ahead trading and power control for hybrid wind-hydrogen plants with multi-agent reinforcement learning. Appl. Energy 401: 126588. https://dx.doi.org/10.1016/j.apenergy.2025.126588, meer Avila, F.J.J.; Verstraeten, T.; Daems, P.J.; Nowe, A.; Helsen, J. (2025). A Methodology for Turbine-Level Possible Power Prediction and Uncertainty Estimations Using Farm-Wide Autoregressive Information on High-Frequency Data. Energies (Basel) 18(14): 3764. https://dx.doi.org/10.3390/en18143764, meer Daenens, S.; Verstraeten, T.; Daems, P.; Nowe, A.; Helsen, J. (2025). Spatio-temporal graph neural networks for power prediction in offshore wind farms using SCADA data. Wind Energy Science 10(6): 1137-1152. https://dx.doi.org/10.5194/wes-10-1137-2025, meer Jamil, F.; Peeters, C.; Verstraeten, T.; Helsen, J. (2025). Leveraging signal processing and machine learning for automated fault detection in wind turbine drivetrains. Wind Energy Science 10(9): 1963-1978. https://dx.doi.org/10.5194/wes-10-1963-2025, meer Vervlimmeren, I.; Chesterman, X.; Verstraeten, T.; Nowe, A.; Helsen, J. (2025). Scalable SCADA-driven failure prediction for offshore wind turbines using autoencoder-based NBM and fleet-median filtering. Wind Energy Science 10(11): 2615-2637. https://dx.doi.org/10.5194/wes-10-2615-2025, meer Chesterman, X.; Verstraeten, T.; Daems, P.J.; Nowé, A.; Helsen, J. (2023). Overview of normal behavior modeling approaches for SCADA-based wind turbine condition monitoring demonstrated on data from operational wind farms. Wind Energy Science 8(6): 893-924. https://dx.doi.org/10.5194/wes-8-893-2023, meer Daems, P.-J.; Peeters, C.; Matthys, J.; Verstraeten, T.; Helsen, J. (2023). Fleet-wide analytics on field data targeting condition and lifetime aspects of wind turbine drivetrains. Forschung im Ingenieurwesen-Engineering Research 87(1): 285-295. https://dx.doi.org/10.1007/s10010-023-00643-0, meer Nejad, A.R.; Keller, J.; Guo, Y.; Sheng, S.; Polinder, H.; Watson, S.; Dong, J.; Qin, Z.; Ebrahimi, A.; Schelenz, R.; Gutiérrez Guzmán, F.; Cornel, D.; Golafshan, R.; Jacobs, G.; Blockmans, B.; Carroll, J.; Koukoura, S.; Hart, E.; McDonald, A.; Natarajan, A.; Torsvik, J.; Moghadam, F.K.; Daems, P.-J.; Verstraeten, T.; Peeters, C.; Helsen, J. (2022). Wind turbine drivetrains: state-of-the-art technologies and future development trends. Wind Energy Science 7(1): 387-411. https://dx.doi.org/10.5194/wes-7-387-2022, meer Vemuri, A.; Buckingham, S.; Munters, W.; Helsen, J.; van Beeck, J. (2022). Sensitivity analysis of mesoscale simulations to physics parameterizations over the Belgian North Sea using Weather Research and Forecasting - Advanced Research WRF (WRF-ARW). Wind Energy Science 7(5): 1869-1888. https://dx.doi.org/10.5194/wes-7-1869-2022, meer Daems, P.-J.; Verstraeten, T.; Peeters, C.; Helsen, J. (2021). Effects of wake on gearbox design load cases identified from fleet-wide operational data. Forschung im Ingenieurwesen-Engineering Research 85: 553-558. https://hdl.handle.net/10.1007/s10010-021-00444-3, meer Helsen, J. (2021). Review of research on condition monitoring for improved O&M of offshore wind turbine drivetrains. Acoustics Australia 49(2): 251-258. https://dx.doi.org/10.1007/s40857-021-00237-2, meer Verstraeten, T.; Nowe, A.; Keller, J.; Guo, Y.; Sheng, S.W.; Helsen, J. (2019). Fleetwide data-enabled reliability improvement of wind turbines. Renew. Sust. Energ. Rev. 109: 428-437. https://dx.doi.org/10.1016/j.rser.2019.03.019, meer El-Kafafy, M.; Devriendt, C.; Guillaume, P.; Helsen, J. (2017). Automatic tracking of the modal parameters of an offshore wind turbine drivetrain system. Energies (Basel) 10(4): 574. https://dx.doi.org/10.3390/en10040574, meer
Peer reviewed publicaties (14) [show]
Ally, S.; Verstraeten, T.; Nowe, A.; Helsen, J. (2025). Optimal day-ahead trading and power control for a hybrid wind-hydrogen plant with multi-agent reinforcement learning. Journal of Physics: Conference Series 3025: 012022. https://dx.doi.org/10.1088/1742-6596/3025/1/012022, meer Daenens, S.; Verstraeten, T.; Daems, P.; Nowe, A.; Helsen, J. (2025). Power Prediction in Offshore Wind Farms using Transferable Multi-Task Graph Neural Networks. Journal of Physics: Conference Series 3016: 012021. https://dx.doi.org/10.1088/1742-6596/3016/1/012021, meer Ivanova, T.; Porchetta, S.; Buckingham, S.; Helsen, J.; van Beeck, J.; Munters, W. (2024). Investigating North Sea Precipitation Variability: Implications for Offshore Wind Energy Siting and Condition Assessments. Journal of Physics: Conference Series 2767: 062009. https://dx.doi.org/10.1088/1742-6596/2767/6/062009, meer Kestel, K.; Jamil, F.; Matthys, J.J.; Vratsinis, K.; Sterckx, J.; Marini, R.; Peeters, C.; Helsen, J. (2024). Offshore field experimentation for novel hybrid condition monitoring approaches. Journal of Physics: Conference Series 2745: 012009. https://dx.doi.org/10.1088/1742-6596/2745/1/012009, meer Kestel, K.; Peeters, C.; Vratsinis, K.; Matthys, J.J.; Sterckx, J.; Daems, P.J.; Helsen, J. (2024). Experimental investigation of the relation between operating conditions and offshore wind turbine drivetrain dynamics. Journal of Physics: Conference Series 2875: 012020. https://dx.doi.org/10.1088/1742-6596/2875/1/012020, meer Marini, R.; Vratsinis, K.; Daems, P.; Verstraeten, T.; Helsen, J. (2024). Insights in wind field reconstruction from two nacelles' LiDAR in the same offshore wind farm. Journal of Physics: Conference Series 2875: 012014. https://dx.doi.org/10.1088/1742-6596/2875/1/012014, meer Van Binsbergen, D.; Verma, A.; Nejad, A.; Helsen, J. (2024). Modeling of rain-induced erosion of wind turbine blades within an offshore wind cluster. Journal of Physics: Conference Series 2875: 012040. https://dx.doi.org/10.1088/1742-6596/2875/1/012040, meer Van Binsbergen, D.; Daems, P.; Verstraeten, T.; Nejad, A.; Helsen, J. (2024). Performance comparison of analytical wake models calibrated on a large offshore wind cluster. Journal of Physics: Conference Series 2767: 092059. https://dx.doi.org/10.1088/1742-6596/2767/9/092059, meer Van Binsbergen, D.; Daems, P.; Verstraeten, T.; Nejad, A.; Helsen, J. (2024). Scalable SCADA-Based Calibration for Analytical Wake Models Across an Offshore Cluster. Journal of Physics: Conference Series 2745: 012014. https://dx.doi.org/10.1088/1742-6596/2745/1/012014, meer Vemuri, A.; Porchetta, S.; Munters, W.; Gebel, J.; Nejad, A.; Helsen, J.; van Beeck, J. (2024). Integrating COAWST and OpenFAST for wind turbine loading. Journal of Physics: Conference Series 2767: 052032. https://dx.doi.org/10.1088/1742-6596/2767/5/052032, meer Vratsinis, K.; Pauscher, L.; Daems, P.; van Beeck, J.; Helsen, J. (2024). Impact of inflow characteristics on the instantaneous power production using detrended fluctuation analysis. Journal of Physics: Conference Series 2767: 092071. https://dx.doi.org/10.1088/1742-6596/2767/9/092071, meer Robbelein, K.; Daems, P.-J.; Verstraeten, T.; Noppe, N.; Weijtjens, W.; Helsen, J.; Devriendt, C. (2023). Effect of curtailment scenarios on the loads and lifetime of offshore wind turbine generator support structures. Journal of Physics: Conference Series 2507: 012013. https://dx.doi.org/10.1088/1742-6596/2507/1/012013, meer Koukoura, S.; Peeters, C.; Helsen, J.; Carroll, J. (2020). Investigating parallel multi-step vibration processing pipelines for planetary stage fault detection in wind turbine drivetrains. Journal of Physics: Conference Series 1618(2): 022054. https://dx.doi.org/10.1088/1742-6596/1618/2/022054, meer Helsen, J.; Gioia, N.; Peeters, C.; Jordaens, P.J. (2017). Integrated condition monitoring of a fleet of offshore wind turbines with focus on acceleration streaming processing. Journal of Physics: Conference Series 842: 012052. https://dx.doi.org/10.1088/1742-6596/842/1/012052, meer
Boekhoofdstukken (9) [show]
Peeters, C.; Antoni, J.; Leclère, Q.; Helsen, J. (2021). Performance analysis of tacholess rotation speed estimation methods for condition monitoring of gearboxes of offshore wind farm, in: ASME 2021 3rd International Offshore Wind Technical Conference. pp. V001T01A019. https://dx.doi.org/10.1115/IOWTC2021-3567, meer El-Kafafy, M.; Gioia, N.; Guillaume, P.; Helsen, J. (2019). Long-term automatic tracking of the modal parameters of an offshore wind turbine drivetrain system in standstill condition, in: Di Maio, D. (Ed.) Rotating machinery, vibro-acoustics & laser vibrometry, volume 7. pp. 91-99. https://hdl.handle.net/10.1007/978-3-319-74693-7_9, meer Gioia, N.; Daems, P.J.; Peeters, C.; Guillaume, P.; Helsen, J.; Medico, R.; Deschrijver, D. (2019). Gaining insight in wind turbine drivetrain dynamics by means of automatic operational modal analysis combined with machine learning algorithms, in: ASME 2019 38th International Conference on Ocean, Offshore and Arctic Engineering - Volume 10: Ocean Renewable Energy. pp. 7, meer Gioia, N.; Daems, P.J.; Peeters, C.; El-Kafafy, M.; Guillaume, P.; Helsen, J. (2019). Influence of the harmonics on the modal behavior of wind turbine drivetrains, in: Di Maio, D. (Ed.) Rotating machinery, vibro-acoustics & laser vibrometry, volume 7. pp. 231-238. https://hdl.handle.net/10.1007/978-3-319-74693-7_22, meer Peeters, C.; Verstraeten, T.; Nowé, A.; Daems, P.-J.; Helsen, J. (2019). Advanced vibration signal procesing using edge computing to monitor wind turbine drivetrains, in: ASME 2019 2nd International Offshore Wind Technical Conference. pp. 6, meer Gioia, N.; Peeters, C.; Daems, P.J.; Guillaume, P.; Helsen, J. (2018). Dealing with harmonics in continuous modal analysis, in: Desmet, W. et al. Proceedings of ISMA2018 - International Conference on Noise and Vibration Engineering & USD2018 - International Conference on Uncertainty in Structural Dynamics. pp. 2819-2828, meer El-Kafafy, M.; Colanero, L.; Gioia, N.; Devriendt, C.; Guillaume, P.; Helsen, J. (2017). Modal parameters estimation of an offshore wind turbine using measured acceleration signals from the Drive Train, in: Niezrecki, C. (Ed.) Structural Health Monitoring & Damage Detection, Volume 7. pp. 41-48. https://dx.doi.org/10.1007/978-3-319-54109-9_5, meer Feremans, L.; Cule, B.; Devriendt, C.; Goethals, B.; Helsen, J. (2017). Pattern mining for learning typical turbine response during dynamic wind turbine events, in: ASME 2017 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. Volume 1: 37th Computers and Information in Engineering Conference. pp. 1-9. https://dx.doi.org/10.1115/DETC2017-67910, meer Helsen, J.; De Sitter, G.; Jordaens, P.J. (2016). Long-term monitoring of wind farms using big data approach, in: IEEE BigDataService 2016. Second IEEE international conference on big data computing service and applications, Oxford, United Kingdom. pp. 265-268. https://dx.doi.org/10.1109/BigDataService.2016.49, meer
Overige publicatie [show]
Helsen, J.; Peeters, C.; Doro, P.; Ververs, E.; Jordaens, P.J. (2017). Wind farm operation and maintenance optimization using big data, in: IEEE BigDataService 2017. The Third IEEE International Conference on Big Data Computing Service and Applications, San Francisco, 6 – 10 April 2017. pp. 179-184. https://dx.doi.org/10.1109/BigDataService.2017.27, meer