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机器视觉检测在“机械制造工艺”实验教学中的应用

Application of Machine Vision Detection in Experimental Teaching of“Mechanical Manufacturing Process”
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摘要 【目的】针对传统“机械制造工艺”课程中检测手段滞后于工业自动化、智能化需求的问题,提出将机器视觉技术融入实验教学的改革方案。【方法】基于企业实际生产中减速器关键零部件的质量检测需求,设计开发了机械制造工艺参数机器视觉检测实验项目。通过搭建图像采集系统,引导学生进行光源选择、参数调节与图像处理,实现对零部件精度的高效检测。【结果】学生在视觉检测运维方面的实践能力得到提升,对打光原理和参数调节工作流程的理解也更为深入。【结论】这一改革能将理论教学与产业前沿技术紧密结合,有效培养学生的实践能力,契合制造业智能化升级对高素质技术技能人才的需求。 [Objective]Aiming at the problem that the detection methods in the traditional“Mechanical Manufacturing Process”course lag behind the needs of industrial automation and intelligence,a reform scheme of integrating machine vision technology into experimental teaching is proposed.[Method]Based on the quality inspection requirements of key components of decelerator in the actual production of enterprises,the machine vision inspection experiment project of mechanical manufacturing process parameters was designed and developed.By building an image acquisition system,students are guided to select light sources,adjust parameters and process images to achieve efficient detection of parts accuracy.[Result]Students’practical ability in visual inspection operation and maintenance was improved,and their understanding of the lighting principle and parameter adjustment workflow was more in-depth.[Conclusion]This reform can closely combine theoretical teaching with industrial cutting-edge technology,effectively cultivate students’practical ability,and meet the needs of intelligent upgrading of manufacturing industry for high-quality technical and skilled talents.
作者 彭辰晨 焦祥 王骏 Peng Chenchen;Jiao Xiang;Wang Jun(Dean’s Office,Wuxi University of Technology,Wuxi 214121,China;School of Automobile and Traffic Engineering,Wuxi University of Technology,Wuxi 214121,China;School of Mechanical Engineering,Wuxi University of Technology,Wuxi 214121,China)
出处 《南方农机》 2026年第6期186-189,共4页
基金 江苏省高等教育教改研究课题(2025JGZD213) 2025年江苏省高校教育信息化研究课题(2025JSETKT213) 江苏省高校实验室工作研究课题(GS2024BZZ42) 无锡市软科学研究课题(KX-25-B30)。
关键词 机器视觉 减速器 工艺参数 HALCON machine vision decelerator process parameters Halcon
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