BLEEPID

Towards improved reliability and reduced costs of offshore wind by blade-leading-edge erosion prediction and drone-based inspection

Introduction

Leading edge erosion of offshore wind blades has drastic impact on maintenance costs and operational energy production and may lead to unwanted microplastics in the environment. Herein, we will develop fundamental image capturing and camera techniques, combined with quantitative wear analysis from experimental erosion testing and multi-physics modelling combining CFD-FSI impact and subsurface fatigue modelling. These advances will enable accurate drone-based inspections of offshore wind blades, and thus optimize maintenance planning and extent the lifetime of the blade.

Context

By 2030, wind energy should yield an annual energy production of 25 TWh green electricity, hereby covering 25-30% of the Belgian electricity demand. Leading-edge erosion (LEE) is a severe erosive wear mechanism which involves progressive material removal from the blade-tip leading edges, due to (sub-)surface fatigue. The repeated highspeed impact of water droplets induces severe pressure shock-waves in the blade material leading to initiation, propagation and coalescence of cracks and eventually material loss, pit formation, delamination and disintegration of the structural integrity. Although wind turbines are designed and built for an operational lifespan of 25 years at maximum energy capacity, current generation of turbines require often extensive maintenance after 5-10 years due to severe LEE and reduced energy production.

Today inspection of wind turbine blades is mostly performed manually by personnel on-site. Drone-based inspections using high-resolution camera techniques become increasingly more popular and may provide valuable data to support such costly decisions concerning maintenance and repair. A lot can be gained since the impact of LEE for the Belgian wind farms is substantial: 1) drastic impact on O&M, (2) energy production loss due to changing drag and lift coefficients and (3) marine pollution due to breaking away of microplastics and polymeric materials.

Goal, approach and results

The project aims to improve the maintenance planning and operation control of offshore wind farms, by using camera-equipped drones to remotely inspect the status of blades and make accurate, quantitative measurements of the erosive wear using accurate images combined with fundamental wear characterization using both experiments and modelling. Four objectives are identified which contribute to mitigating LEE:

To develop image-capturing and analysis methods for high-accurate drone-based LEE inspection. To contribute to reliable predictive maintenance tools, by developing both adequate data-driven and physics-based models for the description and prediction of the evolution of leading-edge erosion based on a current blade-state and precipitation parameters. To provide detailed insight in the interplay of liquid droplet impact on representative leading edge protections using controlled experiments and multi-physics modelling, with the aim to improve those materials in the future or to provide minimum LEP specifications to the wind-park owners. To develop a framework and model to evaluate the socio-economic impact of the newly developed LEE detection and prediction models in terms of levelized cost of energy (LCOE) and their carbon footprint. Simulate the socio-economic impact of these new models on the Princess Elisabeth offshore wind farm development zone. Within the project Sirris develops a framework and model to evaluate the socio-economic impact of the newly developed LEE detection and prediction models in terms of levelized cost of energy (LCOE) and their carbon footprint. The socio-economic impact of these new models will be simulated on the Princess Elisabeth offshore wind farm development zone.

Results

Journal publications

Sterckx, Jonathan, et al. “Accurate and Robust 3D Reconstruction of Wind Turbine Blade Leading Edges from High-Resolution Images.” AUTOMATION IN CONSTRUCTION, vol. 175, 2025, doi:10.1016/j.autcon.2025.106153.
Sterckx, Jonathan, et al. “Segmentation and Quantification of Surface Defects in 3D Reconstructions for Damage Assessment and Inspection.” IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING, vol. 22, 2025, pp. 19439–50, doi:10.1109/TASE.2025.3593967.

Conference publications

Sterckx, Jonathan, et al. “BladeR : Scalable, Shape-Guided 3D Reconstruction of Wind Turbine Blades from UAV Imagery.” Proceedings of the 21st International Conference on Computer Vision Theory and Applications: Volume 3 : VISAPP, 2026, pp. 119–30, doi:10.5220/0014309700004084.
Nambiar, V. R., Degroote, J., De Waele, W., & Fauconnier, D. (2026, May). Surface Stresses During High-Speed Droplet Impact on Pitted Surfaces. In Journal of Physics: Conference Series (Vol. 3224, No. 7, p. 072012). IOP Publishing https://doi.org/10.1088/1742-6596/3224/7/072012
Nambiar, V. R., Shadmani, A., Degroote, J., De Waele, W., & Fauconnier, D. (2025). Blade leading edge erosion protection: high-speed rain droplet impact pressure and resulting damage evolution in hyper-viscoelastic materials. In Wind Energy Science Conference 2025, Nantes. Wind Energy Science Conference.http://hdl.handle.net/1854/LU-01K7SA7XKTPX90KVEVVJ8KSFG1
Shadmani, A., Fauconnier, D., & De Waele, W. (2026). Continuum damage model for the polyurethane coating of wind turbine blades. Procedia Structural Integrity, 77, 221-228, https://doi.org/10.1016/j.prostr.2026.01.030
Conings.B et al., “Quantifying the LCOE impact of leading edge erosion in offshore wind farms”, submitted for presentation at the WindEurope Annual Event 2027 (Copenhagen). (https://windeurope.org/annual2027/

Master Dissertations

Verstockt W., Shadmani, A., Fauconnier, D., & De Waele, W. (2024-2025). Surrogate modeling for fatigue life prediction of coating erosion on a wind turbine blade leading edge. Master’s Thesis.
Keters, J. Investigation of Aerodynamic Performance of Eroded Wind Turbine Blades. Master Thesis. Ghent University (2026)
Coen, A. Generation and Characterization of Droplets for Erosion Testing. Master Thesis. Ghent University (2026)

Posters

i-Know Innovation Day 2023 (https://iknow.ugent.be/)
FEARS 2024 (https://fears.ugent.be/)
Poletto, J.C., et al. “Design of an Experimental Setup for Investigation of Liquid Impingement Erosion”. Poster presentation at Ocean Tribology at the Low Countries Conference (OTLC), 2026
Poletto, J.C., et al. “Design of an Experimental Setup for Quantifying High-Velocity Droplet
Impact Forces”. Poster accepted for presentation at the World Tribology Congress (WTC), 2026.
Shadmani, A., Fauconnier, D., & De Waele, W. (2024). Blade leading edge erosion damage due to droplet impact. 2024 FEA Research Symposium, Abstracts. Presented at the 22nd Faculty of Engineering and Architecture Research Symposium (FEARS 2024), Ghent, Belgium. https://doi.org/10.5281/zenodo.15077027
Ramachandran Nambiar, V., De Waele, W., Degroote, J., & Fauconnier, D. (2023). CFD-FSI modelling of wind turbine blade leading-edge erosion. 2023 FEA Research Symposium, Abstracts. Presented at the Faculty of Engineering and Architecture Research Symposium (FEARS) 2023, Ghent, Belgium.

Leaflet

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BLEEPID workshop

On 21/05/2026 the BLEEPID project organized a workship on how drone inspections, image analysis and predictive modelling help detect erosion earlier, optimise maintenance and improve offshore wind turbine reliability. Through concrete cases and project results from the BLEEPID project, experts from industry and research shared the latest developments in blade protection and inspection technologies.

The workshop brought together a wide range of perspectives. A few examples:

Leading edge protection systems can be highly robust, even under demanding impact conditions (even hail!).
Nevertheless, leading edge erosion is strongly site-specific and can still surprise the most seasoned expert, making generic assumptions risky.
Short, severe weather events can contribute disproportionately to lifetime erosion damage.
Erosion is not limited to the affected blade itself; its aerodynamic impact can propagate through the wake and influence turbines further downstream.
Erosion-safe curtailment only becomes attractive when operators can trust the rain signal; highly local precipitation data is therefore key to avoiding unnecessary production losses.

The event made clear that, although effective solutions already exist, further R&D remains highly valuable to better understand, predict and mitigate leading edge erosion in real offshore and onshore conditions. It also highlighted concrete starting points for new collaborations at the interface of materials, sensing, modelling, maintenance and wind farm operations.

BLEEPID WORKSHOP: More information and full program can be found here.