| Summary: | 碩士 === 國立臺北科技大學 === 機電整合研究所 === 101 === In today''s fast-changing market, 3C products, the entire supply chain is required to quickly design products and manufacturing goods, but in the screws, nuts and other traditional industries, can not escape or to engage in the use of human quality inspection work, making the product yield and labor costs expenses necessarily proportional. In order to effectively solve shaped pattern detection problem within the nut, this study proposes a framework for the use of backlash (Zero Backlash) reducer precision six-axis robotic arm, combined with the binary image processing and Otsu (Otsu exhibition of) Statistics thresholding (Threshold) decided to France for the nut pattern detection system. And through the experiment to test the feasibility of this architecture. The purpose of this study is to use high-precision six-axis robotic arm with machine vision, enhance industrial circles shaped nut, nut blind hole detection technology, if by this framework to replace the existing artificial vision defect detection methods, namely, can improve the detection of various artificial missing, substantially reduced over the last sampling or artificial visual misjudgment, and thus enhance the detection yield and ensure product quality and consistency.
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