共查询到19条相似文献,搜索用时 187 毫秒
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现代工厂中通常需要对工件特征进行判断,然后在平面内对工件进行分类放置。为了能高效快速地识别、筛选工件,采用了机器视觉技术,并将视觉技术应用在二自由度的并联机器人中,设计了一个基于视觉筛选的并联机器人平面抓取系统。视觉控制器对相机传送过来的工件图像进行处理,根据提取的工件的特征进行分类,并确定工件在视觉坐标系中的坐标。视觉处理器将坐标等信息传送给NJ控制器,同时在NJ控制器里运用ST语言编写程序实现机械臂的运动控制,并对运动过程进行3D仿真。仿真结果显示,通过机器视觉和并联机器人的结合,可以实现对工件进行精确的识别、抓取和放置。该系统可应用于根据物体形状不同进行分类的场合,并对研究机器视觉和并联机器人有一定的实用价值。 相似文献
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为了解决电容器生产过程中外观由人工检测带来的劳动强度大、出错率高、效率低下等问题,设计一款基于机器视觉技术结合PLC控制技术的自动外观检测系统。根据电容器外观会出现包装缺陷、字符标识缺陷,设计了以支撑箱体、视觉检测系统、动作执行部分构成的系统平台。视觉检测系统运用合理图像处理算法,结合计算机系统来实现高效图像识别判断。动作执行部分根据视觉检测系统数据信息在PLC控制器作用下实现动作。根据试验结果表明:设计的外观自动检测系统操作简单、稳定可靠,对电容器外观检测的准确率达到100%,大大提高了检测效率,可用于电容器外观检测。 相似文献
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该文以西门子S7-200 Smart PCL为控制核心,构建了一套基于机器视觉的工件自动分拣系统。该系统由控制模块、传输模块、人界交互模块、机器视觉模块组成,首先利用机器视觉技术识别出待分拣工件的特征,然后PLC根据机器视觉识别结果控制传送带动作将工件传送至不同产品盒,实现工件的自动分拣。实验结果表明,该生产线的分拣误判率低于0.4%,满足工业生产的要求。 相似文献
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为了解决电子元件蜂鸣器出厂时人工质检效率低、容易伤害分拣人员听觉等问题,设计了基于机器视觉的电子元件在线质检分类系统。该系统主要由自动上料、视觉检测、声音检测、电极控制和下料控制这5个部分组成,由PLC主控制器、OpenMV视觉检测模块、声音识别模块以及步进电机等配合完成蜂鸣器的自动上料、检测和等级分类功能。经过现场调试及应用表明,该控制系统提高了蜂鸣器的质检分类效率,其效率是人工质检的1.9倍,准确率提高了9.4%,每台设备至少替代3名工人,节约了企业的成本。 相似文献
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几何尺寸精度是影响工件质量的关键因素。针对熔融沉积成型连续制造过程,提出了一种基于机器视觉技术的几何质量在线检测方法。利用CCD图像传感器构建了熔融沉积成型过程图像采集系统;采用图像处理技术获取工件轮廓信息,完成以像素为单位的几何尺寸测量。通过尺寸标定将图像尺寸转化为工件的实际物理尺寸,从而可以与设计模型的理论尺寸进行比较,计算制造误差,为生产者判断熔融沉积成型工件几何质量是否满足要求提供了新的思路。 相似文献
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Development of a real-time laser-based machine vision system to monitor and control welding processes 总被引:2,自引:2,他引:0
Wei Huang Radovan Kovacevic 《The International Journal of Advanced Manufacturing Technology》2012,63(1-4):235-248
In this study, a laser-based machine vision system is developed and implemented to monitor and control welding processes. The system consists of three main modules: a laser-based vision sensor module, an image processing module, and a multi-axis motion control module. The laser-based vision sensor is designed and fabricated based on the principle of laser triangulation. By developing and implementing a new image processing algorithm on the platform of LabVIEW, the image processing module is capable of processing the images captured by the vision sensor, identifying the different types of weld joints, and detecting the feature points. Based on the detected feature points, the position information and geometrical features of the weld joint such as its depth, width, plates mismatch, and cross-sectional area can be obtained and monitored in real time. Meanwhile, by feeding these data into the multi-axis motion control module, a non-contact seam tracking is achieved by adaptively adjusting the position of the welding torch with respect to the depth and width variations of the weld joint. A 3D profile of the weld joint is also obtained in real time for the purposes of in-process weld joint monitoring and post-weld quality inspection. The results indicate that the developed laser-based machine vision system can be well suited for the measurement of weld joint geometrical features, seam tracking, and 3D profiling. 相似文献
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饮料液位自动检测系统设计 总被引:3,自引:0,他引:3
为了提高饮料液位检测的效率,介绍了一种新型的瓶装饮料液位自动检测系统。该系统采用基于机器视觉的检测方法,采用CCD作为检测元件。并基于LabVIEW和IMAQ Vision,开发出了对饮料瓶进行图像获取、图像检测识别的软件。按识别结果进行分拣,从而摆脱了人工分拣的缺点,提高了检验的效率,实现了塑料瓶装饮料罐装线的全自动、非接触和在线检测。研究结果表明,该系统能有效地检测出饮料的液位位置,并判断灌装是否合格,具有准确率高、运行稳定、检验速度快等优点。 相似文献
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硅棒特征点三维坐标视觉检测技术研究 总被引:1,自引:0,他引:1
针对人工接触式硅棒参数检测中存在的耗时、低效、误检等问题,提出一种采用四CCD机器视觉系统作为硅棒参数实时检测的非接触式测量方案。系统基于多目视觉检测原理,以四CCD多目视觉检系统作为机器视觉检测前端数据采集模块,拍摄待测硅棒表面轮廓图像信息。相邻两CCD构成正交双目交汇数据采集子模块,子模块基于正交双目交汇测量原理实时采集两路含有目标空间信息的数字图像数据并保存到上位机。上位机图像处理系统读取采集图像,完成多目相机标定,特征点提取、同名点匹配以及视差计算后提取出目标特征点三维坐标。该检测技术有效避免了人工主观因素造成的漏检、错检,满足实时在线检测要求,实现了硅棒特征点空间三维坐标高精度检测的目的。 相似文献
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Xiangqian Peng Youping Chen Wenyong Yu Zude Zhou Guodong Sun 《The International Journal of Advanced Manufacturing Technology》2008,39(11-12):1180-1189
Quality control is a crucial issue in a float glass factory, and defects existing in float glass can dramatically depress glass grade. Manual inspection in float glass quality control cannot catch up with the development of float glass industry, and automatic glass defect inspection has been a trend. An online defects inspection method for float glass based on machine vision is presented in this paper, and a distributed online defect inspection system for float glass fabrication is realized. This method inspects defects through detecting the change of image gray levels caused by the difference in optic character between glass and defects. A series of image processing algorithms are set up around the analysis of glass image and the requirements of online inspection system such as reliability, real-time, and veracity. Image filtration based on gradient direction is used to filter noise and reserve the source information of defects. Downward threshold based on adaptive surface removes the background composed with stripes and strengthens defect features. Distortion part and core part of defects are obtained through fixed threshold and OTSU algorithms with gray range restricted, respectively. The fake defects (insects, dust, etc.) are eliminated based on the texture of real defects. The application of an inspection system based on this method in Wuhan glass factory proves this inspection method is effective, accurate, and reliable. 相似文献
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