理管机机器视觉摄像机结构设计
|
摘要
针对目前纺织业中理管机效率低、准确率和响应速度慢等问题,以理管机为研究对象,通过分析理管机的工作原理和机器视觉检测技术在理管机的应用,完成视觉系统结构设计以及软件设计。利用光学、摄像机理论知识根据纱管的特征以及理管机的机械特征,应用光学知识设计新的摄像机采集视频图像的位置和角度。该优化设计能够根据纱管和背景的移动采集到清晰的图像,利用图像处理软件,通过背景差分法获取前景图,以此对理管机的理管动作快速验证。结果表明,所设计的理管机机器视觉光源和摄像机可以采集到清晰有效的视频图像,使理管机能高效、准确、快速地进行理管动作,结构系统稳定。
Aiming at the problems of low efficiency,low accuracy and slow response of pipe cutting machine in textile industry at present,this paper takes the pipe machine as the research object,and analyzes the working principle of the pipe cutting machine and the application of machine vision inspection technology in the pipe machine.Complete visual system structure design and software design.Based on the theoretical knowledge of optics and camera,the position and angle of the new camera to capture video images are designed according to the characteristics of the gauze tube and the mechanical features of the pipe mechanism.The optimal design can capture clear images according to the movement of the gauze tube and background and obtain foreground map by background difference method by using image processing software.In this way,the operation of the pipe machine is quickly verified.The results show that the designed machine vision light source and camera can capture clear and effective video images,so that the function of pipe management is efficient,accurate and fast,and the structure system is stable.
Aiming at the problems of low efficiency,low accuracy and slow response of pipe cutting machine in textile industry at present,this paper takes the pipe machine as the research object,and analyzes the working principle of the pipe cutting machine and the application of machine vision inspection technology in the pipe machine.Complete visual system structure design and software design.Based on the theoretical knowledge of optics and camera,the position and angle of the new camera to capture video images are designed according to the characteristics of the gauze tube and the mechanical features of the pipe mechanism.The optimal design can capture clear images according to the movement of the gauze tube and background and obtain foreground map by background difference method by using image processing software.In this way,the operation of the pipe machine is quickly verified.The results show that the designed machine vision light source and camera can capture clear and effective video images,so that the function of pipe management is efficient,accurate and fast,and the structure system is stable.
引文
[1]徐永志.海马集体落纱细纱机长车分体式自动理管机使用体会[J/OL].纺织器材.
[2]陈睿,徐安进,吴小艳.理管机的研究与设计[J].机电产品开发与创新,2012,25(03):43-44.
[3]武筱婷.江阴凯业自动络筒理管机通过鉴定[J].纺织机械,2016(01):21.
[4]高玲.凯业理管机成减少用工好帮手[N].中国纺织报,2016-09-05(008).
[5]唐萍,陆立秋.HM-LG380B型集体落纱细纱机集中理管机的研制[J].纺织器材,2016,43(03):65-66+64.
[6]袁清珂,张振亚,吴晖辉,等.基于机器视觉系统的自动检测系统设计与开发[J].组合机床与自动化加工技术,2014(11):119-121.
[7]秦亚航,苏建欢,余荣川.机器视觉技术的发展及其应用[J].科技视界,2016(25):153-154.
[8]王国庆,张团善,杨斌,范盼飞,陈家鑫,何文莉,张西平.基于CAN总线的横机静电消除系统检测[J].西安工程大学学报,2017,31(01):65-70.
[9]赖伊琦,刘益民,陈锦儒.机器视觉系统中的光源控制器的设计与研究[J].电脑知识与技术,2015,11(14):195-196.
[10]朱宝伟.机器视觉中的光源照明设计[J].电子科技,2013,26(03):80-82.
[11]李俊.机器视觉照明光源关键技术研究[D].天津理工大学,2007.
[12]尚会超,杨锐,段梦珍,等.机器视觉照明系统的关键技术分析[J].中原工学院学报,2016,27(03):16-21.
[13]陈志特.机器视觉照明光源技术要点分析[J].河南科技,2014(02):63.
[14]刘巧玲,陈丽娜,余华恩,柯华恒,梁秀玲.可变焦距机器视觉镜头光学系统设计[J].应用光学,2015,36(02):199-205.
[15]肖春建.机器识别的全自动服装模板缝纫技术的若干思考[J].纺织报告,2017(5):27-28.
[16]李华琛.基于opencv图像边缘检测技术[J].数字技术与应用,2016(11):40+42.
[17]王福斌,李迎燕,刘杰,陈至坤.基于Open CV的机器视觉图像处理技术实现[J].机械与电子,2010(06):54-57.
[2]陈睿,徐安进,吴小艳.理管机的研究与设计[J].机电产品开发与创新,2012,25(03):43-44.
[3]武筱婷.江阴凯业自动络筒理管机通过鉴定[J].纺织机械,2016(01):21.
[4]高玲.凯业理管机成减少用工好帮手[N].中国纺织报,2016-09-05(008).
[5]唐萍,陆立秋.HM-LG380B型集体落纱细纱机集中理管机的研制[J].纺织器材,2016,43(03):65-66+64.
[6]袁清珂,张振亚,吴晖辉,等.基于机器视觉系统的自动检测系统设计与开发[J].组合机床与自动化加工技术,2014(11):119-121.
[7]秦亚航,苏建欢,余荣川.机器视觉技术的发展及其应用[J].科技视界,2016(25):153-154.
[8]王国庆,张团善,杨斌,范盼飞,陈家鑫,何文莉,张西平.基于CAN总线的横机静电消除系统检测[J].西安工程大学学报,2017,31(01):65-70.
[9]赖伊琦,刘益民,陈锦儒.机器视觉系统中的光源控制器的设计与研究[J].电脑知识与技术,2015,11(14):195-196.
[10]朱宝伟.机器视觉中的光源照明设计[J].电子科技,2013,26(03):80-82.
[11]李俊.机器视觉照明光源关键技术研究[D].天津理工大学,2007.
[12]尚会超,杨锐,段梦珍,等.机器视觉照明系统的关键技术分析[J].中原工学院学报,2016,27(03):16-21.
[13]陈志特.机器视觉照明光源技术要点分析[J].河南科技,2014(02):63.
[14]刘巧玲,陈丽娜,余华恩,柯华恒,梁秀玲.可变焦距机器视觉镜头光学系统设计[J].应用光学,2015,36(02):199-205.
[15]肖春建.机器识别的全自动服装模板缝纫技术的若干思考[J].纺织报告,2017(5):27-28.
[16]李华琛.基于opencv图像边缘检测技术[J].数字技术与应用,2016(11):40+42.
[17]王福斌,李迎燕,刘杰,陈至坤.基于Open CV的机器视觉图像处理技术实现[J].机械与电子,2010(06):54-57.