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Vision-Based Sorting Systems for Transparent Plastic Granulate
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This paper describes an automated vision-based system that uses a camera and air jets to sort defective transparent polycarbonate plastic granules at high speed. Better sorting technology supports higher-quality plastic recycling, which could reduce the amount of low-quality plastic that ends up as environmental waste.
Granulate material sorting is a mature and well-developed topic, due to its presence in various fields, such as the recycling, mining, and food industries. However, sorting can be improved, and artificial intelligence has been used for this purpose. This paper presents the development of an efficient sorting system for transparent polycarbonate plastic granulate, based on machine vision and air separation technology. The developed belt-type system is composed of a transparent conveyor with an integrated vision camera to detect defects in passing granulates. The vision system incorporates an industrial camera and backlight illumination. Individual particle localization and classification with the k-Nearest Neighbors algorithm were performed to determine the positions and conditions of each particle. Particles with defects are further separated pneumatically as they fall from the conveyor belt. Furthermore, an experiment was conducted whereby the combined performances of our sorting machine and classification method were evaluated. The results show that the developed system exhibits promising separation capabilities, despite numerous challenges accompanying the transparent granulate material.
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When a large batch of papers lands in the Atlas, we read through it and send a short write-up of what stood out.