Automated Machine Vision System for Recognition and Sorting of Small Gears скачать в хорошем качестве

Automated Machine Vision System for Recognition and Sorting of Small Gears

MECH 898 – Master’s Project Student: Gustavo Baréa Supervisor: Prof. B.W. Surgenor Kingston, ON - April 2017 An automated machine-vision-based system for the recognition and sorting of small gears was designed, assembled and tested. This report documents the design of the system and presents experimental performance results. Nine experiments were conducted to analyze the effects of changing hardware and software parameters, including: conveyor speed, gear feed rate, classification, and identification score thresholds. The conclusion is that the system can achieve a maximum system accuracy of 97% at a feed rate of 40 parts/min, for a given set of parameter settings. With different parameter settings, an accuracy of 96% can be achieved at a feed rate of 65 parts/min, which is the maximum feed rate possible.