TITLE
USING IMAGE PROCESSING TECHNIQUES FOR PART CLASSIFICATION
AUTHOR(S)
Aydın GULLU, M. Ozan AKI
ABSTRACT
In industrial automation, it is used with various sensors for detection. Digital sensors are widely used because they are economical and easy to process. There are digital sensors that detect various materials for part detection. There is a FESTO part sorting station at Trakya University İpsala Vocational School. At the end of the production line, the color and structure of the part is detected and classified by industrial sensors. The part is detected by two optical sensors and the color of the part is determined according to the light reflected from the part. After color detection, it is checked whether the piece is metal or not by means of an inductive sensor. According to the information coming from these three sensors, the parts are classified as black, red and metallic. Instead of this
sensor combination, a camera was used in this study. The color of the part is detected by image processing. In addition, thanks to the camera, part thickness and diameter were also detected. Classification and quality control of the parts were provided with the camera. In the study, the camera works connected to the computer. The classification station is controlled by PLC. Image processing data was transferred to the PLC with a microcontroller card.
DOI
PAGES
161-166
DOWNLOAD
https://unitechsp.tugab.bg/images/2023/4-KS/s5_p168_v2.pdf
How to cite this article:
Aydın GULLU, M. Ozan AKI, USING IMAGE PROCESSING TECHNIQUES FOR PART CLASSIFICATION, Proceedings of International Scientific Conference “UNITECH 2023” – Gabrovo, 161-166