Computer Vision System for Ginseng Drying - Softcover

Martynenko, Alex

 
9783639024500: Computer Vision System for Ginseng Drying

Inhaltsangabe

A control system for multi-stage ginseng drying, based on real-time identification of moisture and quality changes, was developed. Computer-vision system provided real-time imaging of area shrinkage and colour changes. Shrinkage was identified by extracting of the green plane from the RGB color space, while colour changes- from the HSI color space. Shrinkage-moisture and colour-quality relationships were experimentally developed over the entire range of drying conditions in isothermal and non-isothermal drying. Relational models were used as components of control system. Data from computer vision system were used to generate relevant signals to low-level controller for temperature adjustment according to actual moisture content and quality. It enabled to start drying with the predictive model and then re-evaluate the drying conditions on the basis of feedback information from computer-vision system. Testing of a pilot batch dryer with an embedded virtual controller showed robustness and reliability of control, which provided drying to target moisture content 0.1 g/g (db) with high-standard quality.

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Reseña del editor

A control system for multi-stage ginseng drying, based on real-time identification of moisture and quality changes, was developed. Computer-vision system provided real-time imaging of area shrinkage and colour changes. Shrinkage was identified by extracting of the green plane from the RGB color space, while colour changes- from the HSI color space. Shrinkage-moisture and colour-quality relationships were experimentally developed over the entire range of drying conditions in isothermal and non-isothermal drying. Relational models were used as components of control system. Data from computer vision system were used to generate relevant signals to low-level controller for temperature adjustment according to actual moisture content and quality. It enabled to start drying with the predictive model and then re-evaluate the drying conditions on the basis of feedback information from computer-vision system. Testing of a pilot batch dryer with an embedded virtual controller showed robustness and reliability of control, which provided drying to target moisture content 0.1 g/g (db) with high-standard quality.

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