SpectX, in collaboration with TNO, GE Vernova, and LM Wind Power, will launch a two-year project to detect sub-surface defects in wind turbine blades using drone X-ray inspection. The results will be integrated into a digital twin model developed by TNO to improve blade life predictions.
SpectX, alongside Avular and Eindhoven University of Technology, has developed an aerial inspection system capable of capturing X-ray images of wind turbine blades. This technology will be tested in 2025, with images analysed using AI-driven image processing to identify defects.
While SpectX's system can replace traditional rope-access inspections, the process is still time-consuming compared to visual inspections, which provide far less data. To streamline this, the consortium is developing a targeted inspection strategy, utilising the digital twin’s predictive capabilities. The digital twin will pinpoint areas of potential concern, directing drones to inspect specific regions. This continuous feedback loop will enhance accuracy and reduce inspection times.
As part of the project, SpectX will deploy X-ray drones to detect internal defects in the TIADE research turbine in the Netherlands, collecting data to train their AI models. TNO will focus on developing methods to prioritise inspection areas and validate defect detection. Together, the team will establish communication protocols to optimise drone operations, with contributions from GE Vernova and LM Wind Power, who will provide expertise on blade defects and access to the TIADE turbine.
