{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,21]],"date-time":"2026-04-21T22:49:40Z","timestamp":1776811780186,"version":"3.51.2"},"reference-count":25,"publisher":"European Society of Computational Methods in Sciences and Engineering","issue":"6","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JCM"],"published-print":{"date-parts":[[2023,12,15]]},"abstract":"<jats:p>A new automatic lock screw machine for LED lamp has been researched in the paper, which is based on the immune clone algorithm. Firstly, the robot automatic lock screw system has been setup. Vision sensor captured LED lampshade images in real-time. Median filtering operation has been performed to the captured images. On this basis, a new image segmentation method based on the immune clone algorithm has been researched. The antibody and antigen of LED lampshade image have been defined. The immune affinity function has been setup at the same time. Several artificial immune operators have been designed, which can be used to obtain the optimum image segmentation threshold value in real time. The final results showed that the optimum image threshold value can been obtained after less than ten times iterative computation. Compared with the traditional Ostu method, the new method can reduce the disturbance information around the threaded hole, which made basis for threaded hole recognition and location.<\/jats:p>","DOI":"10.3233\/jcm226968","type":"journal-article","created":{"date-parts":[[2023,12,19]],"date-time":"2023-12-19T12:23:25Z","timestamp":1702988605000},"page":"3081-3091","source":"Crossref","is-referenced-by-count":0,"title":["Research of immune clone algorithm applying in the LED lamp automatic lock screw workstation"],"prefix":"10.66113","volume":"23","author":[{"given":"Dukun","family":"Ding","sequence":"first","affiliation":[{"name":"Dongguan Intelligent Manufacturing Engineering Technology Research Center, Dongguan Polytechnic, Dongguan, Guangdong, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jianxin","family":"Deng","sequence":"additional","affiliation":[{"name":"Guangxi Key Lab of Manufacturing System & Advanced Manufacturing Technology, Guangxi University, Nanning, Guangxi, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hui","family":"Ye","sequence":"additional","affiliation":[{"name":"Dongguan Intelligent Manufacturing Engineering Technology Research Center, Dongguan Polytechnic, Dongguan, Guangdong, China"},{"name":"ABB (China) Limited Guangzhou Branch, Guangzhou, Guangdong, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"55691","reference":[{"key":"10.3233\/JCM226968_ref1","doi-asserted-by":"crossref","unstructured":"Frustaci F, Spagnolo F, Perri S, Cocorullo G, et al. 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