In this work an Automatic Optical Inspection (AOI) system has been developed to diagnose Printed Circuit Boards (PCB) mounted in Surface Mounting Technology (SMT). The diagnosis task is handled as a classification problem with a neural network approach. We will present results on the diagnosis of visible defects on a SMT-PCB. A CCD camera acquires a number of images of the circuit under test and a neural network associates these images to a defect class. A set of procedures makes automatic the set-up and the diagnosis phases. The developed system seems to be a good solution in an industrial application because of the low cost, very fast diagnosis and easiness to set-up and handle.
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