Sulzer Schmid, a Swiss company pioneering UAV technology for rotor blade inspections, and NNAISENSE, a world leading artificial intelligence specialist, have partnered to develop an artificial intelligence engine to automatically detect rotor blade damages on wind turbine. This leapfrog technology is expected to bring the twin benefits of improving the productivity and consistency of blade inspection processes.
With this new development effort, the two partners are aiming to build the industry’s most powerful Artificial Intelligence engine able to recognize damages based on inspection image material. The initial version will be able to flag all areas of concern on any given damaged blade. Ensuing upgrades will add other capabilities such as the ability to establish damage categories and severity levels.
“Maintaining the structural integrity of rotor blades is critical to maximizing energy output and ensuring the safe operation of wind turbines. We are convinced that we will be able to transfer our extensive expertise in surface defect recognition from other industries to the wind industry and are looking forward to our cooperation with Sulzer Schmid, an innovator in its own space”, commented Faustino Gomez, CEO of NNAISENSE.
The autonomously flying drones of the 3DX™ Inspection Platform of Sulzer Schmid assure high-definition quality and consistent image acquisition time as well as 100% blade coverage while minimizing human errors and operational risks. The cutting-edge image assessment tools of the platform ensure detailed and efficient damage assessment. With the support of an AI-enabled inspection software, the review work of blade experts will be greatly facilitated. Instead of having to review the entire surface of the blades, they will simply need to focus on the pre-selected areas of concern. This technology progress will not only significantly boost the productivity of the reviewing teams but will also improve the quality of damage annotation processes.
“Maximising end-to-end productivity is a key success factor in the highly competitive market of wind turbine inspection solutions. Thanks to our collaboration with NNAISENSE, we will be able to push the envelope in this area and significantly advance the automation capabilities of our inspection platform”, explained Christof Schmid, COO and Co-founder of Sulzer Schmid.
Tom Sulzer, CEO and Co-founder of Sulzer Schmid, concluded: “We are very excited about our collaboration with NNAISENSE, a true leader in the visual recognition of surface damages by means of AI. This will further enhance the added value we provide for our customers and partners”.
About Sulzer & Schmid Laboratories AG
Founded in 2015 by Tom Sulzer and Christof Schmid, Zurich-based Sulzer Schmid is at the forefront of innovation in the energy service sector. Recognizing the potential for unmanned aerial vehicle (UAV) technology to redefine industrial grade inspections, the two entrepreneurs and their engineering team have developed an end-to-end inspection platform that produces high-quality inspection results with ease – precisely, repeatably, efficiently. The development of the dedicated 3DX™ Inspection Platform started in 2015. Since those days, thousands of autonomous inspection missions have been conducted based on its technology throughout Europe and the US, each underpinned by a commitment to the highest quality, efficiency, safety and ground-breaking use of technology. www.sulzer-schmid-labs.ch/
About NNAISENSE SA
NNAISENSE is a Swiss-American startup, founded in 2014, that leverages the 25-year proven track record of one of the leading research teams in machine learning to bring true AI to industrial inspection, modeling, and process control. From manufacturing and robotics to autonomous vehicles, NNAISENSE is delivering custom neural network solutions through cutting-edge research and real world know-how. Its chief scientist and co-founder, Dr. Jürgen Schmidhuber, is a pioneer in the field of neural networks and responsible for some of the key scientific breakthroughs, such as Long Short-Term Memory, that have help ignite the recent wave of interest in AI. https://nnaisense.com/