Title: Ai-Enabled Automatic Inspection in Wind Turbine Blade Manufacturing: Technology Validation and Demonstration

Authors: Juan Su & Scott Blake

DOI: 10.33599/nasampe/s.24.0135

Abstract: Current best practice in the manufacture of large wind turbine blades is labor-intensive and includes manual in-process inspection of composites layup. This approach leaves blade manufacturing subject to human errors that, if left uncorrected, compromise the mechanical integrity of the blade. To minimize undetected layup errors, a developmental project is underway to adapt machine vision-based automatic inspection technology to the challenging process of wind blade manufacturing and the harsh environs of an industrial facility. This paper discusses the demands that blade manufacturing places on automatic inspection technology, including large focal distances and fields of view, environmental variability such as vibration and luminosity levels within the production facility, capture of ultra-high quality images, AI-enabled real-time image analysis and feedback for corrective actions, and documentation that includes stitching of images to generate a panoramic representation of the entire blade. The paper also reports on the current status of a developmental project to validate and demonstrate the technology (TRL 4) for rapid advancement into an industrial environment (TRL 5-7).

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Conference: SAMPE 2024

Publication Date: 2024/05/20

SKU: TP24-0000000135

Pages: 14

Price: $28.00