Magnus Munk Jensen
PhD fellow | Electronic Systems | Aalborg University
About
I am a PhD fellow working on condition monitoring of main bearings in wind turbines. My research focuses on enhancing machine learning and deep learning methods by incorporating physical insights and model-based knowledge.
I also investigate how to integrate data from multiple sensors in controlled environments and apply this knowledge to real-world, noisy settings with limited sensor availability.
I am currently affiliated with Aalborg University.
My research is supported by Innovation Fund Denmark and Siemens Gamesa Renewable Energy.
Research Interests
- Structurual Condition Monitoring
- Physics Enhanced Machine Learning and Deep Learning
- Acoustics
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Publications
• Application of pseudo-anomaly generation in unsupervised fault diagnosis of wind turbine bearings under changing operating conditions, International Operational Modal Analysis Conference (IOMAC), 2025