大范围液位实时自动跟踪测量系统

针对传统液位测量方法的精度低、速度慢、测量范围受限制等问题,设计了一套基于视觉图像处理的高精度、快速的液位自动测量系统,它适用于测量范围大、液位变化速度快的实时液位测量。该系统以CCD摄像机采集的液位和钢尺图像为基础,通过钢尺刻度识别、钢尺刻线及液位识别三大识别模块完成液位高度测量,根据液位高度反馈控制电机带动CCD相机跟随液位实现实时自动跟踪测量。为了提高算法的识别速度,增强算法的鲁棒性,该系统采用了NCC(the normalized cross correlation)模板匹配数字识别方法,在刻线识别和液位识别过程中充分利用了图像的灰度特征和钢尺的结构特征完成识别。实验结果表明该测量系统的算法有着较高的鲁棒性以及较快的测量速度,可以完成精度在0.1mm以内的液位测量。     

卡尔曼滤波焊缝跟踪控制

在视觉传感的电弧自动焊接过程中,需要根据视觉信息来控制电弧准确地跟踪焊缝.由于强烈的弧光干扰,使得从焊接区图像中直接提取电弧与焊缝的偏差信息十分困难.为此提出一种利用熔池图像质心和卡尔曼滤波来间接获取电弧与焊缝偏差的方法.选择熔池图像质心作为状态向量,建立基于图像质心的状态方程和焊缝位置测量方程.利用卡尔曼滤波消除过程噪声和测量噪声的影响,通过对熔池图像质心的状态估计,准确获取焊缝位置以及电弧与焊缝之间的偏差量,为自动焊接过程的焊缝跟踪控制提供准确信息.焊接试验结果表明,利用卡尔曼滤波方法可有效降低过程噪声和测量噪声的影响,从而提高焊缝跟踪控制精度.     

百叶轮抛磨叶片微结构区域识别及路径拼接方法研究

叶片型面具有曲率突变特性,需进行分区域加工,其微结构区域的精确识别和抛磨路径拼接是提高叶片表面质量一致性的关键。针对此类问题,提出一种依据截面线切向量夹角变化识别前、后缘微结构区域,根据截面线法向量配准识别叶根过渡圆弧微结构区域的方法,即根据百叶轮最大加工带宽度和抛磨点匹配法分别实现前、后缘和叶根过渡圆弧微结构区域与叶盆、叶背抛磨路径的拼接。仿真及实验结果表明,该方法相较传统圆弧识别方法,能更有效保留微结构区域轮廓信息,相比未考虑路径拼接的抛磨方式,抛磨后叶片型面轮廓精度提高 49.52%,表面粗糙度提高 57.31%,加工质量一致性提高 7.15%和 11.55%,证实了微结构区域的识别及路径拼接可有效提高叶片加工质量的一致性。     

基于现场总线式焊缝检测复合传感器设计

介绍了一种传感器前置的焊缝检测与跟踪控制方法.由GMR电桥和涡流传感器构成焊缝检测复合传感器,GMR电桥进行高度检测,涡流传感器的差动测量绕组进行焊缝中心偏差检测.通过补偿绕组对测量绕组输出信号进行补偿,消除错边对相位和幅值的影响;通过软件校正方法,消除高度变化对信号幅度的影响.建立FIFO数据队列保存焊炬与前置传感器...     

基于深度学习的多旋翼无人机单目视觉目标定位追踪方法

针对无人机对目标的识别定位与跟踪,本文提出了一种基于深度学习的多旋翼无人机单目视觉目标识别跟踪方法,解决了传统的基于双目摄像机成本过高以及在复杂环境下识别准确率较低的问题。该方法基于深度学习卷积神经网络的目标检测算法,使用该算法对目标进行模型训练,将训练好的模型加载到搭载ROS的机载电脑。机载电脑外接单目摄像机,单目摄像头检测目标后,自动检测出目标在图像中的位置,通过采用一种基于坐标求差的优化算法进行目标位置准确获取,然后将目标位置信息转化为控制无人机飞行的期望速度和高度发送给飞控板,飞控板接收到机载电脑发送的跟踪指令,实现对目标物体的跟踪。试验结果验证了该方法可以很好的进行目标识别并实现目标追踪     

液位实时自动跟踪测量系统

针对传统液位测量方法的精度低、速度慢、测量范围受限制等问题,设计了一套基于视觉图像处理的高精度、快速的液位自动测量系统,它适用于测量范围大、液位变化速度快的实时液位测量.该系统以CCD摄像机采集的液位和钢尺图像为基础,通过钢尺刻度识别、钢尺刻线及液位识别三大识别模块完成液位高度测量,根据液位高度反馈控制电机带动CCD相...     

基于多CPU的目标识别与跟踪系统设计

设计了一个实时图像采集、目标识别与跟踪系统;系统功能包括图像采集、运动估计、目标识别、摄像机云台控制等;系统功能主要由3片CPU完成,其中由2片DSP构成的图像采集处理单元实现两路图像采集、目标识别和运动估计,识别和估计结果通过系统总线送给跟踪控制系统;由1片ARM构成的目标跟踪控制系统对2路摄像机的云台和镜头等实现实时控制,使目标一直位于视场中;该系统采样率为10fps,当运动目标的距离在100 m以内,速度小于15 m/s时,可以实现实时识别与跟踪;该系统可以应用于视频监控等应用领域。     

计算机视觉在焊缝跟踪控制中的应用

研究一种基于计算机视觉的焊缝跟踪控制系统,重点论述焊缝图象分割和边缘提取的理论方法,通过对视觉传感器CCD检测到的弧焊区图象进行处理来准确地识别焊缝位置,从而有效地提高焊缝跟踪精度。     

焊接机器人焊缝自动跟踪系统

本文提出了一种焊接机器人焊缝自动跟踪系统用以实现焊枪对焊缝的实时自动跟踪。系统中应用激光焊缝传感器测量焊缝的位置,并采用Fuzzy-P双模分段控制进行焊缝的纠偏。DSP作为系统的核心控制器产生控制信号,驱动焊枪横向步进电机和纵向步进电机动作,调整焊枪实时跟踪焊缝。实验证明,基于双模控制的焊缝自动跟踪系统可以实现焊接机器人焊枪对焊缝的实时自动跟踪。该系统完全满足实际焊接工程的需要。     

基于双模控制的焊接机器人焊缝自动跟踪系统

该文提出了一种基于双模控制的焊接机器人焊缝自动跟踪系统.系统中应用新一代激光焊缝传感器测量焊缝的位置,并采用Fuzzy-P双模分段控制进行焊缝的纠偏.系统中采用DSP作为核心控制器产生控制信号,驱动焊枪横向步进电机和纵向步进电机动作,实现焊接机器人焊枪对焊缝的实时自动跟踪.实验证明,基于双模控制的焊缝自动跟踪系统可以实现焊接机器人焊枪对焊缝的实时自动跟踪.该系统完全满足实际焊接工程的需要.     

水泥砂浆衬里补口作业机器人光整作业装置的研制

本文研制了水泥砂浆衬里补口作业机器人, 首先介绍了机器人系统组成及工作原理,然后详 细分析了其光整作业装置,其设计巧妙,具有结构紧凑、一电机多功用的复合功效、光整功 能完善可靠等显著特点,实验证明是一种理想的水泥砂浆衬里光整作业装置,在工程应用中 具有推广价值．     

结构光在集装箱顶角加强板焊缝定位中的应用

针对集装箱顶角加强板的焊接特点,设计了一种基于结构光的自动焊缝定位方法。该方法主要有两个特点:一是将摄像机安装在机器人上,使光轴垂直工作平面,通过比较面积大小来获得深度信息,从而将三维信息的获取问题转化为二维信息的提取,并利用仿射变换获得空间信息;二是利用激光器与摄像机相配合的方式进行定位,由于激光束在焊接环境中的特征明显,可降低图像处理的难度。具体实现过程是利用两条线激光打在加强板的一个角上,在加强板和顶板之间的焊缝处出现转折,通过对激光条纹的有效处理,获得4对转折点的图像坐标,然后拟合直线求出加强板的焊接初始位置及方向,再结合事先制作的图像模板将加强板的其他特征点逐一求出。该系统有效地利用了激光器的优势,可靠地解决了加强板焊缝的自动定位问题。     

Autonomous Acquisition of Seam Coordinates for Arc Welding Robot Based on Visual Servoing

Autonomous acquisition of seam coordinates is a key technology for developing advanced welding robot. This paper describes a position-based visual servo system for robotic seam tracking, which is able to autonomously acquire the seam coordinates of the planar butt joint in the robot base frame and plan the optimal camera angle before welding. A six-axis industrial robot is used in this system, which has an interface for communicating with the master computer. The developed visual sensor device is briefly presented that allows the charge-coupled device (CCD) cameras to rotate about the torch. A set of robust image processing algorithms are proposed so that no special requirements of light source are needed in this system. The feedback errors of this servo system are defined according to the characteristics of the seam image, and the robust tracking controller is developed. Both the image processing program and tracking control program run on the master computer. The experimental results on straight line seam and curve seam show that the accuracy of the seam coordinates acquired with this method is more adequate for high quality welding process.     

Acquisition of Weld Seam Dimensional Position Information for Arc Welding Robot Based on Vision Computing

Recognition and identification of weld environment and seam dimensional position by computer vision is a key technology for developing advanced autonomous welding robot. Aiming at requirements for recognition of weld seam image characteristics, this paper first presents an improved algorithm of subpixel edge detection based on Zernike moments. Comparing with the Ghosal’s original algorithm, the improved algorithm deals with mask effect and first derivative model on edge gradient direction so that it has the strong robust to noise, self-thinning ability and higher locating precision. An algorithm based on ZMs to extract line is also proposed, the comparative results with SHT and RHT show the method has the highest calculation speed and accuracy. The stereovision technology is developed to identify dimensional position of weld seam by computing dimensional coordinates of the weld seam. According to characteristics of weld seam, view field scope model and stereovision model based on baseline are studied and a stereo matching method is presented. In order to evaluate the algorithms and models presented in this paper, a welding robot systems with single camera fixed on the weld torch end-effector has been established for the robot to identify the dimensional position of typical weld seam by one-item and two-position method. The experiment results on S-shape and saddle-shape weld seams show that the vision computing method developed in this paper can be used for acquiring weld seam dimensional position information in welding robot system. Thus the welding path is mapped before the welding operation is executed.     

色噪声下卡尔曼滤波焊缝跟踪算法与试验研究

精确控制激光束使其始终对中并跟踪焊缝是保证激光焊接质量的前提．以大功率光纤激光焊接Type304不锈钢为试验对象,研究一种有色噪声环境下应用卡尔曼滤波最优状态估计预测激光束与焊缝路径偏差的方法．使用高速红外视觉传感器摄取焊接区红外热像,提取焊缝位置参数并构成状态向量,建立基于焊缝位置参数的系统状态方程和焊缝位置测量方程．针对系统动态噪声为有色噪声,通过扩展状态变量的方法建立有色噪声环境下的卡尔曼滤波算法,对焊缝位置进行最优状态估计并得到最小均方差条件下的焊缝偏差最优预测值,消除系统噪声对焊缝偏差测量的影响．焊接试验结果表明新方法可有效抑制有色噪声干扰并提高焊缝跟踪精度．     

Real-Time Seam Tracking Technology of Welding Robot with Visual Sensing

A seam tracking system with visual sensing free from calibration was developed for the robot applied in gas tungsten arc welding. A visual sensor with double-layer filter system was researched for the different levels of the welding current. An image processing in C+?+ language was developed to extract the seam trajectory and the offset of the torch to the seam in the welding images of aluminum alloys plates with grooves. The rectifying rule of the robot used in this paper was found based on the experimental data, and the seam tracking controller was also analyzed and constructed. The experimental results on straight line seam and curve seam demonstrated the efficiency of the proposal seam tracking system.     

激光拼焊焊缝跟踪系统视觉检测方法的研究

激光焊接作为一种新的焊接技术,其对焊缝跟踪提出很高的精度要求。本文针对焊缝跟踪系统中视觉检测单元的精度进行了深入分析,分别对跟踪系统视觉单元精度的定义,视觉检测精度控制的原理,图像的采集以及图像处理的方法做了研究,并提出了一种精确的直线焊缝跟踪视觉检测方法。     

A new seam-tracking algorithm through characteristic-point detection for a portable welding robot

The welding task in double-hulled structures in shipyards and in steel-frame structures is hazardous and difficult due to the toxic gas and limited workspace. Therefore, many efforts have been undertaken for automation. The main challenge for automation is the development of a simple and robust seam-tracking algorithm that can be applied to a portable welding robot that operates under irregular and diverse task conditions in the workspace. We developed a seam-tracking algorithm for weaving weld path planning using a laser displacement sensor. The goal of the proposed algorithm is to detect the seam of single-butt welding with manually tack-welded non-zero gaps. The focus is on keeping the algorithm simple and affordable so that it can be applied to portable robots that operate in hazardous fields. The algorithm consists of four steps: scanning, filtering, generation of the reference points, and path planning. In the scanning process, the depth data of a cross-section of the seam profile is obtained. Next, a Gaussian filter is used to remove noise from the raw data. A differential characteristic-point detection algorithm is applied to the filtered data to detect the reference points that represent the shape and location of the gap to be welded. Finally, path planning for single-V butt multi-pass welding is done based on the detected reference points. A portable four-axis welding robot is built using the developed algorithm. The algorithm is validated through welding experiments regarding a single-V butt welding task with a manually tack-welded non-zero gap.