Active Learning Processes for Smart Inspection, Verification Operations and Modelling of Surfaces with Geometrical Deviations

The ISO 17450-2:2012 defines the verification operation. The ISO 17450-1:2011 defines the extracted features and the extraction operations on the “non-ideal surface model or on the real surface of the workpiece”. The ISO 12781-2:2011 and 12180-2:2011 provide dedicated extraction strategies for the flatness and cylindricity. But no real measurement process is explicit here. However, one of the key factors in an inspection plan is the choice of the measurement strategy. Some sampling strategies, such as Hammersley sequence, offer robust and efficient technics to ensure good distribution of measurement points. But measurements are always defined with a “blind sampling strategy”. So, in this paper, the author proposed to use adaptative sampling strategies, based on the Active learning method based on Kriging for the Inspection of Large Surfaces (AK-ILS) and developed an original Active Learning method based on Multi-Layer-Perceptron (AL-MLP), to classify the conform / non-conform parts and to ensure the reconstruction of the surfaces, with smart Skin Models Shapes and a minimal sampling size.