Abstract
This paper describes a particle expert system (PES) that was developed to improve particle classification for burrs, casts, and chips in the automotive production process. Image-processing techniques were deployed to extract particle information and remove noise from industrial filters and lighting systems. An advanced model of a particle classification algorithm (PCA) was built with 12 particle classes and a particle-expert-system (PES) algorithm was developed to train the PCA parameters to achieve the target success rate. The particle expert system will help the user locate the source of particles with high reliability and a stable success rate immediately after image processing and training the PCA parameters.
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