New EUDP project will demonstrate the use of AI-techniques in offshore corrosion management

The PACMAN project (Predictive Automatic Corrosion Management) focuses on predicting the development of corrosion on offshore structures, and with that, being able to predict the needed repair and associated cost of corrosion. The driver in this project is to drastically reduce the number of manual hours, which today makes corrosion detection too time consuming and inefficient. The tools for doing this are: automatic position tagging, improved corrosion detection through more advanced camera technology, improved machine learning methods for visual detection of corrosion in 2D images and automated transfer of 2D image corrosion findings to a 3D interpretation for more efficient handling of these corrosion findings. All of these tools are used in the predictive corrosion management. Essentially, predictive corrosion management concerns severity classification of the found corrosion. The long-term goal involve use cases on offshore structures such as: wind firms, substations and oilrigs.
 
The project partners are the Robotics and Automation Group @AAU, Semco Maritime, TREFOR, IPU, MM Survey ApS and Energy Cluster Denmark.
 
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