WSEAS Transactions on Circuits and Systems
Print ISSN: 1109-2734, E-ISSN: 2224-266X
Volume 23, 2024
PCB Image Defects Detection by Artificial Neural Networks and Resistance Analysis
Authors: ,
Abstract: The approach contains the sequence of algorithms and formulas for image processing. They are single-layer neural networks, thinning, clustering, mathematical image comparison, and measurements of the trace length and width. All these procedures solve the task of selection and separation of the main objects in the printed circuit board: contacts, traces, and defects. The calculated features connect the conductance resistance of traces with the characteristics of defects. Imposing a tolerance on the distributed or concentrated changes of resistance it is possible to mark the defective and suspicious printed circuit boards.
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Keywords: Printed circuit board, chain, trace, defects, clustering, flood-filling, artificial neural networks, skeleton, edge, thinning, cumulative histogram, resistance, width of trace, overlay, tolerance
Pages: 70-83
DOI: 10.37394/23201.2024.23.7