{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,25]],"date-time":"2026-04-25T10:23:13Z","timestamp":1777112593810,"version":"3.51.4"},"reference-count":36,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2020,9,16]],"date-time":"2020-09-16T00:00:00Z","timestamp":1600214400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>An automatic tool-setting and workpiece online detecting system was proposed to study the key technologies of next-generation intelligent vision computerized numerical control (CNC) machines. A computer vision automatic tool-setting system for a CNC machine was set up on the basis of the vision tool-setting principle. A rapid vision calibration method based on the position feedback from the CNC machine was proposed on the basis of the theory of traditional vision system calibration. The coordinate mapping relationship of the image and the CNC machine, the tool-setting mark point on the workpiece, and the tool tip were calibrated. The vision system performance testing and system calibration experiments were performed. Experimental results indicated that the time consumption was 128 ms in image processing. The precision of tool setting and measuring was less than 1 \u03bcm. The workpiece positioning and processing online detection function of the system can completely meet the requirements of visual CNC machine application, and the system has wide application prospects.<\/jats:p>","DOI":"10.3390\/s20185302","type":"journal-article","created":{"date-parts":[[2020,9,16]],"date-time":"2020-09-16T20:44:13Z","timestamp":1600289053000},"page":"5302","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["Computer Vision Tool-Setting System of Numerical Control Machine Tool"],"prefix":"10.3390","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3748-389X","authenticated-orcid":false,"given":"Bo","family":"Hou","sequence":"first","affiliation":[{"name":"Key laboratory of molecular imaging of Chinese Academy of Sciences, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China"}]},{"given":"Congpeng","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Mechanical and Materials Engineering, North China University of Technology, Beijing 100144, China"}]},{"given":"Shoubo","family":"Yang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Precision Opt-mechatronics Technology, Ministry of Education, Beihang University, Beijing 100191, China"}]}],"member":"1968","published-online":{"date-parts":[[2020,9,16]]},"reference":[{"key":"ref_1","first-page":"1134322","article-title":"Micro-milling cutter precise tool setting technology based on discharge sensing","volume":"11343","author":"Hu","year":"2019","journal-title":"Int. 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