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Neural network classification of Fraunhofer diffraction patterns for inspection of fine-pitch electronic components

This paper describes research into a non-contact system for the inspection of fine pitch electronic components on manufactured electronic assemblies. A far-field diffraction pattern from the leads of a tape automated bonding component is captured and stored on a frame store. The diffraction pattern is statistically represented and then classified using an artificial neural network. Results from simulation and experimentation show the feasibility of the technique.