Aluminium Material Inspection

The solution allows for automated analysis of fuselage defects.

As part of the structural analysis for the identification of anomalies in the fuselage assembly process, Reco 3.26 is developing an experimental computer vision system which, using suitably trained convolutional neural networks (CNN Convolutional Neural Network), is able to detect, locate and classify possible defects on aluminum surfaces caused by improper use of assembly tools or abrasive media and / or incorrect rework operations.

The computer vision subsystem developed by Reco 3.26 and enhanced with artificial intelligence techniques and algorithms, receives in input the images and / or information retrieved from the acquisition subsystem, and returns the classification of the defect, if present, together with its location on the 'image.

All Reco 3.26 systems can be easily integrated into the customer's pre-existing infrastructure.


Solution applied for the inspection of the aluminum material in the aeronautics / aerostructures field