Netherlands
I’m an R&D engineer specialized in developing and validating innovative health monitoring methods for offshore wind turbines. My technical background spans the development and validation of virtual strain monitoring applications for offshore wind turbines, which encompasses expertise in e.g. data science, signal-processing, structural modelling/dynamics, system identification, state estimation, optimization, model-calibration as well as extensive experience in working with measurement data. I am experienced in analysing complex systems, turning large datasets into actionable insights, and delivering industry-ready solutions. Alongside technical versaitlity, I bring leadership, collaboration and teaching skills, demonstrated through e.g. supervising 10+ 45 ECTS MSc graduation projects, guiding 100+ M.Sc. students from theory to code, teaching, chairing an international event for 160 participants, contributing to boards as well as building professional and personal communities wherever I go. These experiences strengthened my ability to guide people and teams with clarity and direction, structure challanges, and translating technical complexity into shared understanding. I’m now open to new roles in technology development, innovation, strategy, policy, or research where I can combine diverse/complex challenges with people skills, and contribute to impactful work.
To further increase industry impact, by opening pathways toward low-cost full-farm fatigue monitoring, I implemented a MEMS-IoT-based single-sensor monitoring strategy and verified it on simulated data from a 15 MW turbine. This project entailed an extensive performance benchmark for single and multi-sensor methods and resulted in recommendations on sensor placement, sensor sparsity and performance trade-offs, and handling of quasi-static and dynamic load contributions.
During my stay at VUB, my core topic was the development and validation of model-based virtual sensing frameworks for monitoring the accumulation of full-field fatigue damage without the need for dense sensor layouts. A unique aspect of my work is the use of real vibration data in combination with finite element models based on design documentation. This setup reflects realistic operational constraints and enables industry-relevant insights rather than relying on idealized simulations. Key contributions: development and validation of virtual sensing methods; quality assessment and improvement of optical strain data; validation and sensitivity studies for farm-wide FE modelling and model updating.
Grade: Summa cum laude Supervision: Prof. Dr. ir. Wout Weijtjens, Prof. Dr. ir. Christof Devriendt Title: Practical frontiers in applied model-based virtual strain sensing for offshore wind turbine support structures DOI: https://doi.org/10.5281/zenodo.18418697