- Wind Turbines
- Fault Detection
- Modal Analysis
- +۵ مورد دیگر
Jan Helsen is a Professor of Engineering Technology at Vrije Universiteit Brussel (VUB), leading the Acoustics & Vibrations Research Group. His primary affiliation is within the Faculty of Engineering Technology, focusing on advanced research in renewable energy systems, offshore wind technology, and predictive maintenance. He actively collaborates with industry partners and governmental institutions, as seen in projects like the Belgian Offshore Wind Innovation Centre (2024–2027) and the INSPIRE initiative under the Sustainable Blue Economy Partnership. Helsen’s research emphasizes wind turbine reliability, fault detection algorithms, and AI-driven operational optimization. His work bridges mechanical engineering principles with data science, addressing challenges such as drivetrain health monitoring, wake effect modeling, and hybrid energy systems. Recent contributions include modular deep learning frameworks for wind farm power forecasting and reinforcement learning strategies for hybrid wind-hydrogen plants. He has secured significant funding through projects totaling over €10M, including the €3M ICON (Cloud-edge AI for Offshore Wind O&M) and the €2.5M INSPIRE initiative. Helsen’s team publishes extensively in journals like Mechanical Systems and Signal Processing and Wind Energy Science , with a focus on practical solutions for offshore energy challenges. His lab also pioneered datasets on hyperspectral analysis of additive manufacturing processes, demonstrating interdisciplinary reach. Key collaborations include INSA Lyon (France) for joint PhD programs and the Royal Meteorological Institute for weather simulation studies. Helsen’s work is cited over 1,078 times (h-index 16), reflecting his influence in advancing offshore wind infrastructure resilience and smart energy systems.







