GE Vernova, a prominent player in the wind energy sector, is setting new standards in wind turbine blade manufacturing by deploying cutting-edge AI and robotics technologies for quality inspections. With the world's energy transition heavily relying on wind power, GE Vernova is committed to ensuring that each blade leaving its factories meets the highest quality standards, ultimately contributing to the reliability and longevity of its wind turbines.
The manufacturing process of wind turbine blades is a labor-intensive endeavor, requiring around 2,000 labor hours to produce each blade. Skilled workers meticulously handcraft fiberglass fabric and balsa wood into enormous split pea pod shapes, while tubes suck out air and pump in gallons of resin. To enhance this process, GE Vernova is leveraging AI algorithms that scour each blade's interior, identifying deviations before they are shipped out with a digital quality certificate.
The AI-enabled inspection solution aims to catch deviations early in the process, reducing the risk of more serious issues once the turbine is operational. This proactive approach is expected to minimize costly downtime and enhance the overall lifetime of the critical components, ultimately benefiting power producers and supporting the world's energy transition goals.
GE Vernova's engineers are also employing AI to inspect raw materials before molding and assembly, ensuring consistent quality throughout the manufacturing process. Veronica Barner, renewables director at GE Vernova's Advanced Research Center, emphasizes that the concept of using technology to identify potential issues at the right time is being applied to every critical step in the manufacturing process, guaranteeing that all blades, regardless of their origin, meet the same high-quality standards.
To tackle the challenge of inspecting the massive blades, which can weigh around 20 tons and measure roughly 80 meters long, GE Vernova's Advanced Research engineers have developed a scalable solution that combines state-of-the-art 360-degree digital cameras, computer vision, and AI algorithms. The cameras relay high-quality video feeds of the blade's interior to the cloud, allowing remote engineers to piece together a high-definition montage of the entire surface.
The AI system, trained on tens of thousands of annotated images, autonomously recognizes and flags potential anomalies, empowering human technicians to review the findings and carry out necessary repairs before the blade is shipped. This feedback loop becomes even richer as the technology is deployed to shop factories, providing critical and timely knowledge to the teams working on bringing the blades to life.
To access the blade's interior, GE Vernova has deployed a fleet of robotic remote-operated "crawlers" that serve as all-seeing eyes inside the components. These crawlers, about the size of a two-foot model car, can inch along the blade's full length and scan its inner surface in just 30 minutes, accessing areas that are off-limits to human inspectors.
GE Vernova's vision extends beyond the final inspection stage, as the company aims to embed the concept of using technology to find quality issues throughout the production line. By developing and deploying a series of technologies leveraging AI, GE Vernova seeks to certify the quality of blades at the most critical production steps, ensuring the highest standards are maintained from raw materials to the finished product.
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