摘要
通过对焊缝尺寸测量方法的分析,针对Q345E钢板对接焊和304不锈钢平板堆焊两种焊缝检测要求,以康耐视DS1100系列3D位移传感器作为图像采集设备,通过VEXTA PK569-NA步进电机和KH-01型步进电机控制器搭建滚轴丝杠直线匀速位移平台,采用宜科EB50B8编码器进行速度反馈,并在基于.NET的Cognex Designer2.5视觉工具软件上完成图像处理及尺寸测量。视觉传感器DS1100集成了2D CMOS传感器和线激光发射器,根据激光三角法原理采集图像,并通过以太网连到计算机,将采集的图像传送到计算机Designer软件上。在Designer中进行图像处理系统的搭建、相机参数的设定以及运动平台参数的设置,再借助移动平台扫描运行,获取焊缝成形图像,最后通过计算工具对图像横截面关键点进行标定和测量,得到焊缝尺寸信息。经验证,该系统的检测精度达到检测要求,检测效率大大提高。
According to the analysis of weld size measurement method, in view of the two kinds of weld inspection requirements for Q345 E steel plate butt welding and 304 stainless steel plate surfacing welding, the DS1100 series 3D displacement sensor is taken as the image acquisition equipment, the linear uniform speed displacement platform of the roller screw is formed by VEXTA PK569-NA stepping motor and KH-01 stepping motor controller, the EB50B8 encoder is used for speed feedback, and the Cognex Designer 2.5 based on.NET is used for image processing and dimension measurement. The visual sensor DS1100 integrates a 2 D CMOS sensor and a line laser transmitter, and it collects the image according to the principle of laser triangulation, connects to the computer through Ethernet, and transmits the collected images to the Designer software in the computer. In Designer, the image processing system is set up, the camera parameters and motion platform parameters are set, and the weld forming image is obtained with the help of the moving platform. Finally, the key points of image cross section are calibrated and measured by calculation tools, then the weld size information is obtained. It is verified that the detection accuracy of the system meets the testing requirements and the detection efficiency is greatly improved.
作者
薛彬
孟庆森
褚慧慧
矫爽本
XUE Bin;MENG Qing-sen;CHU Hui-hui;JIAO Shuang-ben(Engineering and Technology R&D Center of Mechanical and Electrical in Colleges of Shandong,Qingdao Binhai University,Qingdao 266555 China;School of Mechanical and Electrical Engineering,Qingdao Binhai University,Qingdao 266555 China;Qingdao Zhongzhuang Vision Automation System Control Co.,Ltd.,Qingdao 266555 China)
出处
《科技创新与生产力》
2020年第1期73-76,共4页
Sci-tech Innovation and Productivity
基金
青岛滨海学院科技计划研究项目（2018KY02）
青岛滨海学院教学改革研究项目（2018JZ01）
