基于NI Vision Assistant的机器视觉在钢球表面检测中的应用

阐述钢球表面检测的意义和机器视觉的基本原理,使用LabVIEW和NI Vision Assistant对所采集的钢球图像进行了处理且做出相应分析.     

基于虚拟仪器的机器视觉在PCB元器件检测中的应用

PCB板的检测是电子设备制造过程中的重要环节,它是产品质量和性能达标的重要保障.为了实现生产过程中缺陷检测的自动化,研究了用机器视觉检测技术检测PCB元器件缺陷的方法.本文使用LaDVIEW、NI Vision Assistant和Vision Builder对所采集的PCB图像进行了处理且做出相应分析.通过实验证明,所讨论的方法对缺陷检测能够达到满意结果.     

LabVIEW Vision在汽车发动机进气管检测系统中的应用

针对汽车发动机进气管中存在杂质及缺陷难以检测的现状,提出了以机器视觉为基础,以LabVIEW的Vision and Motion模块及其附属可视化软件Vision Assistant获取图像信息的检测方法。通过对图像进行预处理、形态学处理、图像分割、高级形态学处理等建立起一个完整的汽车发动机进气管检测系统。实践表明,该检测方法操作合理,检测方便,实用性强,可视化效果好,完全满足检测技术要求。     

应用IMAQ Vision的齿轮测量技术

应用IMAQ Vision将机器视觉技术和虚拟仪器技术相结合,可以快速、准确地进行齿轮在线测量.介绍了基于IMAQ Vision,应用图像直方图分析和LUT变换、几何变换、边缘检测、亚像素精度、模式匹配等图像处理技术的齿轮几何参数测量方法,分析了其中主要IMAQ Vision函数的算法.在LabVIEW平台上开发了实用的齿轮测量机器视觉系统.     

基于机器视觉的尺寸测量方法研究

用CMOS摄像头搭建了简易的机器视觉系统,利用NI Vision Assistant软件实现了对试件线性尺寸和圆弧尺寸的测量,论证了低成本CMOS镜头用于尺寸测量的可行性。     

基于Labview的干电池缺陷检测系统

基于Labview的机器视觉技术对干电池缺陷检测技术进行研究。在Labview环境下,采用第三方图像采集卡对干电池缺陷进行数据采集,运用视觉开发模块IMAQ Vision进行图像处理,结合Machine Vision模块实现图像模式识别,实现干电池缺陷的检测与智能识别。     

机器视觉检测系统在汽车中央电器盒上的应用

介绍汽车中央电器盒总成装配中对装配的部件及字符检测的机器视觉检测系统的应用,并对机器视觉检测系统的原理、图像处理过程和结果进行了阐述。     

直击现场

凌华科技Vision China 2007展示机器视觉整体解决方案2007年6月14日,产业计算机应用平台供货商——凌华科技积极亮相Vision China 2007第四届机器视觉国际展览会。展示的展品包括凌华科技在中国独家代理的Euresys图像采集卡系列和Seritech的工业相机系列,另有     

基于LabVIEW对图像采集与处理技术的研究

分析了机器视觉技术的发展趋势,构建了图像采集和处理系统的架构,并在LabVIEW和Vision软件平台下对图像的采集和处理技术进行了研究,实现了对图像的采集和处理,并描述了图像的二值化、均衡化、滤波等图像处理技术的具体实现方法.     

基于机器视觉的自动化装配系统设计

为了加快中国产业升级,机器视觉和工业机器人是改变手工装配模式的重要手段。机器视觉作为一种用于识别物体、从数字图像中提取和分析物体信息的技术,已被广泛应用于工业生产中。为了进一步推动机器视觉应用于自动化装配系统,文章提出与机器视觉系统相结合的自动装配系统的原型。在机器视觉系统中,开发一系列定位算法,并用图像校准以获得机器人拾取和放置过程的正确坐标。测试表明,系统能够正确检测和识别装配空间的形状和方向,从而实现零件的拾取和放置过程。     

一种用于多轴孔装配的机器人系统研究

针对生产实践中的特殊零件．对机器人总体设计并联手腕设计、在线无接触测量、西门子专用数控系统的二次开发等进行了研究。该机器人基于视觉装配．失用主动柔顺的方法保证零件之间的正确装配关系，有效地提高了装配质量和减少了对人工技能的依赖。     

Robotic automatic assembly system for random operating condition

A vision guided tabletop robotic assembly system is constructed for the random environment automatic assembly purpose. The distributed control structure is designed for this assembly system. A PC is specified as the central control unit for machine vision operation and the harmonization of At89c51 distributed control unit for each axis. The machine vision is introduced to search the locations and measure the size of the assembly parts in the robotic workspace. Then, the central controller commands the robot to pick the part sequentially based on the specified program to complete the automatic assembly process. The model-free fuzzy sliding mode control scheme is embedded in each joint micro controller for simplifying the model based control problem. The central control unit PC communicates with each joint controller by network communication. This assembly system is implemented on a 3 DOF SCARA robot. The experimental results show that the robotic motion control performance is good enough for assembling work; the vision pattern classification and assembly motion paths planning and monitoring are exactly executed by the central control unit. The goal of this robotic random assembly operation is achieved with the appropriate integration of robotic motion control, machine vision, sensor and assembly force detecting techniques.     

基于机器视觉的机械零件测量技术

应用IMAQ Vision软件构建的机械零件测量系统将机器视觉技术和虚拟仪器技术结合在一起，对各种机械零件进行快速准确的在线测量。这里以齿轮为例介绍了测量的技术路线。测量系统综合应用LabVIEW和它的企业链接、信号处理等工具包，将被测对象的图像和数据直接融合到企业的信息流之中。     

Accurate measurement method for tube’s endpoints based on machine vision

Tubes are used widely in aerospace vehicles, and their accurate assembly can directly affect the assembling reliability and the quality of products. It is important to measure the processed tube’s endpoints and then fix any geometric errors correspondingly. However, the traditional tube inspection method is time-consuming and complex operations. Therefore, a new measurement method for a tube’s endpoints based on machine vision is proposed. First, reflected light on tube’s surface can be removed by using photometric linearization. Then, based on the optimization model for the tube’s endpoint measurements and the principle of stereo matching, the global coordinates and the relative distance of the tube’s endpoint are obtained. To confirm the feasibility, 11 tubes are processed to remove the reflected light and then the endpoint’s positions of tubes are measured. The experiment results show that the measurement repeatability accuracy is 0.167 mm, and the absolute accuracy is 0.328 mm. The measurement takes less than 1 min. The proposed method based on machine vision can measure the tube’s endpoints without any surface treatment or any tools and can realize on line measurement.     

基于单目视觉的轴孔零件定位系统设计

针对轴孔零件精密装配过程中单目视觉定位系统的使用困难,设计了一种基于单目视觉的轴孔零件定位系统,提出了基于图像特征的零件倾斜角计算方法,可直接判定零件倾斜姿态.通过对椭圆快速检测算法进行优化,减小噪声影响,实现了高精度检测.最终通过该系统实现了轴孔零件的准确定位,提高了轴孔零件自动装配的成功率.实验证明,提出的方法能够在单目视觉条件下准确得到待装配零件的空间位置信息,满足同轴度要求 １５ μ m 级的轴孔精密装配需求,具有较好的工程应用价值.     

一种新型微装配系统的设计与研制

研究了微小器件装配的特点和计算机视觉反馈引入微装配作业的优势，在此基础上提出了一种新型的微装配系统设计方案，并研制出了样机。整个系统由显微图像采集子系统和微操作子系统两大部分构成，通过计算机将其整合在一起。设计分析和实验表明：该样机可用于尺寸小于1mm的典型微小器件的计算机视觉反馈装配作业研究。     

Small sample parts recognition and localization from unfocused images in precision assembly systems using relative entropy

Recognition and localization of mechanical parts using machine vision is a common approach in precision assembly systems. However, positional inaccuracy in assembly systems often produces unfocused images. Hence, existing methods of part recognition and localization are vulnerable to failure. In this paper, we present a part recognition and localization method, based on relative entropy, which can be applied to small samples. First, a template image is generated based on the contour of the parts and divided into several regions. The intensity distribution of the regions was sampled to generate template features. Then, the captured image is segmented using the Gaussian mixture model and the expectation maximum algorithm to extract the target part in the image. Part features are also generated by sampling the target part image using the template features. Furthermore, an optimization model is established in which the objective function is the sum of the relative entropy between the image features, the template features, and the region matching error correction term. By solving the optimization model, the location of the part can be obtained. The proposed method is compared with the edge and invariant feature-based methods through experiments. The results show that the proposed method has higher robustness and is suitable for the recognition and localization of parts with unfocused images. By using this method, the flexibility and reliability of precision assembly systems can be improved.     

一种微小挠性零件的自动化精密装配系统

为解决具有挠性结构微小零件精密装配的问题,将基于机器视觉的精密测量技术、高分辨率非接触激光位移测量技术等应用到精密装配系统的研制中.设计了用于微小零件夹持的装置,实现了对微小挠性零件拾取、搬运、放置等操作;根据视觉系统测量得到的微小零件与目标位置的偏差,对微小零件水平面内的位置和姿态进行了调整;提出了装配微小零件挠性结构的接触控制方法,该方法通过激光位移传感器非接触测量挠性结构接触变形所引起的微小位移变化,实现了装配过程中垂直方向的精密接触控制;通过在作业机械臂上集成标定模板,实现了装配系统的自动标定.简要介绍了所研制的装配系统组成,并进行了微小挠性零件的装配实验.实验结果表明,微小零件装配的平行度、同轴度误差小于10 μm,挠性结构接触控制偏差为0.6 μm ～0.8 μm,装配精度满足使用要求.