【作者】 张磊；

【导师】 庄春刚；

【作者基本信息】 上海交通大学 ， 机械工程， 2018， 硕士

【摘要】 代表着国家基础制造的能力的汽车制造业是制造业中的重点行业。随着机械加工行业的人工成本越来越高,使用工业机器人替代人工为数控机床或者加工中心进行自动的上下料已成为行业趋势,但只应用传统示教功能的工业机器人系统柔性较低。面对智能制造浪潮的到来,提高自动化生产系统的柔性已经成为自动化生产的关键所在。本文针对汽车空调法兰零件的加工过程开展了柔性自动化系统设计研究。将机器视觉技术引入到自动化生产系统中识别定位散乱零件来料,通过散乱零件定位后的位置信息应用工业机器人对零件进行抓取。首先,介绍了整个机器人自动上、下料系统的整体方案设计,验证得出了适合的整体方案以及机器人的选型、安装方式。以前述整体方案为基础,进行了自动上、下料机构的研发设计,包含了对设计要求的分析、详细的核心机构设计以及机器视觉部件的安装设计。在阐述机器人前端夹具设计过程之后,对比优化得到了最合适的夹具设计方案。为下一步构建完整的机器人数控机床自动上下料系统提供了良好的硬件基础。然后,简要介绍了摄像机标定的方法,在摄像机标定的基础上进行了机器人手眼标定。完成了精确定位位置标定以及精确定位位置机器人工具坐标系旋转中心标定。以前述标定为前提,使用外轮廓形状匹配原理进行图像处理以及坐标变换,为机器人自动上下料提供了理论基础。最后,详细介绍了可编程控制器的控制流程、机器人辅助控制功能以及工控机软件主要的工作流程,并给出了报警流程的设计。在控制系统设计完毕的基础上,对系统进行了各方面精度以及稳定性测试以及产品的标准化。通过测试结果可以得到:基于机器视觉的机器人机床上下料系统能够很好的完成对数控机床的自动上下料,符合各个方面设计要求。更多还原

【Abstract】 As a key industry in the manufacturing,automobile manufacturing represents the basic manufacturing capabilities of a country.As the labor cost are getting higher and higher,it has been a trend to using industrial robots to replace manual labor for CNC machines or machining centers.However,the flexibility of traditional industrial robotic systems is quite low.Confront the challenge of intelligent manufacturing,the key to automated production has been to improve the flexibility of automatic systems.In this paper,the design of flexible automation system is studied for the processing of automobile air-conditioner flange parts.Machine vision technology is introduced to positioning scattered parts of the incoming material of an automated production system,then industrial robot can picking those parts by location.First of all,the project of robot automatic loading and unloading system is introduced,and suitable overall scheme and robot selection and installation are verified.On the basis of the overall plan,the design of the automatic feeding body was carried out,which included the analysis of the design requirements and the detailed design of the core body as well as the installation design of the machine vision components.The design process of robot front-end clamp is expounded,optimization has been done for the most suitable design.It provides the hardware foundation for building a complete machine vision based automatic loading and unloading system.Then,the method of camera calibration is introduced,and the robot hand calibration is carried out on the basis of camera calibration.The calibration of the precise positioning position and rotation center of the robot tool coordinate are completed.With prerequisite calibrations,using contour matching principle to process the images,completing the coordinate transformation for the robot,which provide a theoretical basis for automatic loading and unloading.Finally,it introduces the control flow of programmable controller,the auxiliary control by the robot,the main work flow of IPC software,and the design of alarm flow.On the basis of the control system,the total system was tested in various aspects of accuracy and stability as well as the standardization of the products.Through the test results it can be concluded that the robot machine loading and unloading system based on the machine vision can be a perfect machine feeder,achieve all design requirements.更多还原