Revolutionizing Fiber Composite Material Production with Non-Destructive Automated Detection: The FiberRadar Project

The Fraunhofer Institute for High Frequency Physics and Radar Techniques FHR has developed an innovative method that can automatically and non-destructively monitor and identify defects in fiber composite materials during the production process. This capability was previously impossible, and it is particularly significant in the production of wind turbine rotor blades due to the potential for defects to cause undulation or incorrect and twisted fiber orientation in the material.

Defects in Fiber Composite Materials

Fiber composite materials, used primarily in wind turbine rotor blades, consist mostly of glass fiber-reinforced plastics. If they are not appropriately laid out, defects may occur, which could impact the proper functioning of the blades. Therefore, it is crucial to detect defects during the manufacturing of fiber composite materials.

The FiberRadar Project was a collaboration between Fraunhofer FHR, Ruhr University Bochum, FH Aachen University of Applied Sciences, and Aeroconcept GmbH. The project’s objective was to develop a measurement system that could enable the control of manufactured components with unprecedented precision, exceeding what was previously possible.

The FiberRadar project researchers have achieved a significant breakthrough in non-destructive and automated detection by developing a method for checking the alignment of the lower glass fiber layers. For the first time, a millimeter-wave scanning system comprising a radar, a fully polarimetric robot, and imaging software can identify defects during the production process without damaging the product.

The Radar System

The radar system used in the scanning process sends and receives signals in two polarizations, providing high-resolution imaging of fiber structures, thus making it easier to detect any defects in deeper layers. The use of radar in scanning individual layers enables researchers to identify anomalies in fiber orientation and non-destructively examine the entire material volume.

Refraction compensation is a process that enhances the quality of images used by a scanning system. It is particularly important in reducing unwanted refraction effects in deeper layers, and plays a crucial role in detecting defects in the material.

Failure to detect anomalies in fiber orientation can result in defects in the final product, affecting its performance. However, by utilizing radar technology to scan individual layers, researchers can non-destructively identify anomalies in fiber orientation and examine the entire material volume, thereby ensuring high-quality final product.

The FiberRadar project has developed a measurement system that allows for precise production and control of fiber composite materials, surpassing the levels of accuracy that were achievable previously. By adopting this production method, manufacturers can guarantee superior quality of their final product, ensuring it functions as intended.

In conclusion, the FiberRadar project by the Fraunhofer Institute for High Frequency Physics and Radar Techniques FHR is revolutionizing the production of fiber composite materials, particularly in the manufacturing of wind turbine rotor blades. The project’s non-destructive and automated detection method can efficiently detect any defects during the production process, resulting in a final product that is of high quality and functions as expected.

Explore more

Can Stablecoins Balance Privacy and Crime Prevention?

The emergence of stablecoins in the cryptocurrency landscape has introduced a crucial dilemma between safeguarding user privacy and mitigating financial crime. Recent incidents involving Tether’s ability to freeze funds linked to illicit activities underscore the tension between these objectives. Amid these complexities, stablecoins continue to attract attention as both reliable transactional instruments and potential tools for crime prevention, prompting a

AI-Driven Payment Routing – Review

In a world where every business transaction relies heavily on speed and accuracy, AI-driven payment routing emerges as a groundbreaking solution. Designed to amplify global payment authorization rates, this technology optimizes transaction conversions and minimizes costs, catalyzing new dynamics in digital finance. By harnessing the prowess of artificial intelligence, the model leverages advanced analytics to choose the best acquirer paths,

How Are AI Agents Revolutionizing SME Finance Solutions?

Can AI agents reshape the financial landscape for small and medium-sized enterprises (SMEs) in such a short time that it seems almost overnight? Recent advancements suggest this is not just a possibility but a burgeoning reality. According to the latest reports, AI adoption in financial services has increased by 60% in recent years, highlighting a rapid transformation. Imagine an SME

Trend Analysis: Artificial Emotional Intelligence in CX

In the rapidly evolving landscape of customer engagement, one of the most groundbreaking innovations is artificial emotional intelligence (AEI), a subset of artificial intelligence (AI) designed to perceive and engage with human emotions. As businesses strive to deliver highly personalized and emotionally resonant experiences, the adoption of AEI transforms the customer service landscape, offering new opportunities for connection and differentiation.

Will Telemetry Data Boost Windows 11 Performance?

The Telemetry Question: Could It Be the Answer to PC Performance Woes? If your Windows 11 has left you questioning its performance, you’re not alone. Many users are somewhat disappointed by computers not performing as expected, leading to frustrations that linger even after upgrading from Windows 10. One proposed solution is Microsoft’s initiative to leverage telemetry data, an approach that