基于视觉传感管道焊接机器人跟踪系统研究
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摘要
我国西北地区油气资源丰富,而东部沿海市场需求巨大,这样的产销分离促使管道输送业蓬勃发展。目前管道建设中管道对接环形焊缝的现场焊接多由手工完成,或采用需要人工干预的轨道式自动焊接设备,严重制约了管道建设的发展。因此开展智能化管道焊接机器人研究,提高管道焊接质量和效率,具有巨大的经济效益和社会效益。
管道焊接机器人属特种机器人研究领域。本研究针对大型油气输送管道(直径≥Φ600mm)现场施工条件下对接环形焊缝的自动化焊接技术,在结构光视觉传感器的模型建立及参数选择,焊缝图像的处理方法,移动焊接机器人跟踪控制方法等方面进行深入研究,研制出基于视觉传感的管道焊接机器人焊缝跟踪系统。
本文应用透视成像原理通过坐标变换推导出结构光视觉传感器的模型,建立传感器成像点与被测物上点之间的变换关系。应用光度学理论,结合光学成像系统与带通滤光片的作用,推导出视觉传感器输出灰度图像的弧光干扰模型,指导结构光视觉传感器设计过程中传感检测位置以及摄像机倾角等参数的确定,以减少弧光干扰,有效地提高了焊缝图像的信噪比。
由视觉传感器焊缝图像快速可靠提取焊缝特征信息是实现焊缝跟踪的关键。通过对图像处理方法的深入研究,针对结构光视觉传感器焊缝图像中干扰的特点,采用一维离散LoG(Laplacian of Gaussian)滤波、邻域均值滤波、基于先验知识改进的最大方差阈值分割和标记法小区域去噪组成焊缝图像预处理方法,快速获得清晰的焊缝图像。然后对焊缝图像进行数学形态学细化处理得到焊缝骨架,可靠提取了焊缝特征信息。结果表明,采用这种处理方法结构光视觉传感图像具有良好的抗干扰性,处理一幅像素400×300图像的时间不大于0.08秒,满足焊缝跟踪的需要。
针对滑动转向移动机器人和直角坐标焊枪调整机构组成的管道焊接机器人,应用Lyapunov稳定性理论设计了管道焊接机器人环形运动控制律;提出基于圆柱坐标的管道焊接机器人环形焊接焊缝跟踪算法;为提高焊缝跟踪精度,研究了当管道焊接机器人车轮轴线与管道轴线有偏角时的跟踪补偿方法。
研制出焊枪侧置形式的管道焊接机器人样机,由永磁轮吸附在焊缝一侧的被焊管道上运动,与骑跨在焊缝上的管道焊接机器人相比,使焊缝跟踪精度不受管道对口精度的影响,并可以完成管道弯角对接焊缝的焊接,扩大了其工作范围。
研制出一套结构光视觉传感器,编制了焊缝图像处理软件。基于LabVIEW软件平台研制出能实现图像采集、角度传感器信号采集、伺服电机运动控制等的管道焊接机器人测控系统。
实验表明,基于视觉传感管道焊接机器人跟踪系统可靠性高,满足管道焊接对跟踪系统的要求。
In northwest China there are abundant resources of oil and natural gas, but tremendous market requirement are there in southeast China. So the enormous separation between product and sale promotes of pipeline transportation industry. Recently, the pipeline construction technology relies on manual welding or orbited-welding device manipulated by workman, which enormously restricts the development of pipeline transportation industry. Therefore, development of intelligent pipeline welding robot will bring immense economic and society benefit.
Pipeline welding robot belongs to the research field of special type robotics. Aimed at automatic girth welding of the large diameter pipelines on condition of field operations, researches are lucubrated on modeling and parameters selection of structured light sensor, processing methods of seam images, seam tracking of mobile welding robot. A seam tracking system for girth-welding robot based on vision sensing is developed.
The model of a vision sensor based on structured light is educed with perspective imaging and coordinate transform principle. Using luminosity theory and considering the function of optics imaging system and light filter, the model of sensing image influenced by arc noise is established, with the distance between the arc point and the structured light stripe on the work-piece and the angle between the axis of CCD camera and the plane of structured light. With the model, approaches are derived to decrease arc disturbance and improve quality of sensing images, guiding to optimize the structure parameters of structured light sensors.
Adaptive thresholding segmentation method used Maximal square difference within selected section based on priori information is developed. A compounding including this developed method, one dimension discrete LoG (Laplacian of Gaussian) filter, neighborhood averaging filter, labeling technique for small dollops removal is to be used to pre-process seam images. Then the skeleton of seam is extracted using morphologic thinning. As a result, the characteristic information is extracted rapidly and stably. Experiments show that by using this compounding processing, the seam tracking system acquires powerful anti-jamming ability. Within 0.08s, a 400×300 picxels image can be processed, so it can meet the requirement of field welding.
Aimed at the pipeline welding robot, the controller for girth locomotion is designed using Lyapunov stability theory. A seam tracking arithmetic based on cylinder coordinate is developed aimed at pipeline girth welding robot, and compensate value is calculated when axis of welding robot departs from the pipeline axis.
A prototype of pipeline welding robot with welding torch positioned at one side of welding robot is developed. Attaching on one of welded pipelines by permanent magnet wheels, it avoids effect of the staggered butt joint on precision of seam tracking, compared with the structure straddling on both side of welded pipeline. For an extended work, it can be used on welding of butt joint of two non-coaxial pipelines.
A structured light sensor and the control system using LabVIEW with image picking, inclinometer information picking and servo motors control are taken in practice and the soft program is worked out.
Seam tracking experiment shows the seam tracking system is with high reliability, and meets the requirement of pipeline girth welding.
管道焊接机器人属特种机器人研究领域。本研究针对大型油气输送管道(直径≥Φ600mm)现场施工条件下对接环形焊缝的自动化焊接技术,在结构光视觉传感器的模型建立及参数选择,焊缝图像的处理方法,移动焊接机器人跟踪控制方法等方面进行深入研究,研制出基于视觉传感的管道焊接机器人焊缝跟踪系统。
本文应用透视成像原理通过坐标变换推导出结构光视觉传感器的模型,建立传感器成像点与被测物上点之间的变换关系。应用光度学理论,结合光学成像系统与带通滤光片的作用,推导出视觉传感器输出灰度图像的弧光干扰模型,指导结构光视觉传感器设计过程中传感检测位置以及摄像机倾角等参数的确定,以减少弧光干扰,有效地提高了焊缝图像的信噪比。
由视觉传感器焊缝图像快速可靠提取焊缝特征信息是实现焊缝跟踪的关键。通过对图像处理方法的深入研究,针对结构光视觉传感器焊缝图像中干扰的特点,采用一维离散LoG(Laplacian of Gaussian)滤波、邻域均值滤波、基于先验知识改进的最大方差阈值分割和标记法小区域去噪组成焊缝图像预处理方法,快速获得清晰的焊缝图像。然后对焊缝图像进行数学形态学细化处理得到焊缝骨架,可靠提取了焊缝特征信息。结果表明,采用这种处理方法结构光视觉传感图像具有良好的抗干扰性,处理一幅像素400×300图像的时间不大于0.08秒,满足焊缝跟踪的需要。
针对滑动转向移动机器人和直角坐标焊枪调整机构组成的管道焊接机器人,应用Lyapunov稳定性理论设计了管道焊接机器人环形运动控制律;提出基于圆柱坐标的管道焊接机器人环形焊接焊缝跟踪算法;为提高焊缝跟踪精度,研究了当管道焊接机器人车轮轴线与管道轴线有偏角时的跟踪补偿方法。
研制出焊枪侧置形式的管道焊接机器人样机,由永磁轮吸附在焊缝一侧的被焊管道上运动,与骑跨在焊缝上的管道焊接机器人相比,使焊缝跟踪精度不受管道对口精度的影响,并可以完成管道弯角对接焊缝的焊接,扩大了其工作范围。
研制出一套结构光视觉传感器,编制了焊缝图像处理软件。基于LabVIEW软件平台研制出能实现图像采集、角度传感器信号采集、伺服电机运动控制等的管道焊接机器人测控系统。
实验表明,基于视觉传感管道焊接机器人跟踪系统可靠性高,满足管道焊接对跟踪系统的要求。
In northwest China there are abundant resources of oil and natural gas, but tremendous market requirement are there in southeast China. So the enormous separation between product and sale promotes of pipeline transportation industry. Recently, the pipeline construction technology relies on manual welding or orbited-welding device manipulated by workman, which enormously restricts the development of pipeline transportation industry. Therefore, development of intelligent pipeline welding robot will bring immense economic and society benefit.
Pipeline welding robot belongs to the research field of special type robotics. Aimed at automatic girth welding of the large diameter pipelines on condition of field operations, researches are lucubrated on modeling and parameters selection of structured light sensor, processing methods of seam images, seam tracking of mobile welding robot. A seam tracking system for girth-welding robot based on vision sensing is developed.
The model of a vision sensor based on structured light is educed with perspective imaging and coordinate transform principle. Using luminosity theory and considering the function of optics imaging system and light filter, the model of sensing image influenced by arc noise is established, with the distance between the arc point and the structured light stripe on the work-piece and the angle between the axis of CCD camera and the plane of structured light. With the model, approaches are derived to decrease arc disturbance and improve quality of sensing images, guiding to optimize the structure parameters of structured light sensors.
Adaptive thresholding segmentation method used Maximal square difference within selected section based on priori information is developed. A compounding including this developed method, one dimension discrete LoG (Laplacian of Gaussian) filter, neighborhood averaging filter, labeling technique for small dollops removal is to be used to pre-process seam images. Then the skeleton of seam is extracted using morphologic thinning. As a result, the characteristic information is extracted rapidly and stably. Experiments show that by using this compounding processing, the seam tracking system acquires powerful anti-jamming ability. Within 0.08s, a 400×300 picxels image can be processed, so it can meet the requirement of field welding.
Aimed at the pipeline welding robot, the controller for girth locomotion is designed using Lyapunov stability theory. A seam tracking arithmetic based on cylinder coordinate is developed aimed at pipeline girth welding robot, and compensate value is calculated when axis of welding robot departs from the pipeline axis.
A prototype of pipeline welding robot with welding torch positioned at one side of welding robot is developed. Attaching on one of welded pipelines by permanent magnet wheels, it avoids effect of the staggered butt joint on precision of seam tracking, compared with the structure straddling on both side of welded pipeline. For an extended work, it can be used on welding of butt joint of two non-coaxial pipelines.
A structured light sensor and the control system using LabVIEW with image picking, inclinometer information picking and servo motors control are taken in practice and the soft program is worked out.
Seam tracking experiment shows the seam tracking system is with high reliability, and meets the requirement of pipeline girth welding.
引文
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103 L. Caracciolo, A. D. Luca and S. Iannitti. Trajectory Tracking Control of a Four-Wheel Differentially Driven Mobile Robot. IEEE Int. Conf. Robotics and Automation, Detroit, MI. 1999: 2632–2638
104 D. Pazderski, K. Kozlowski and W. E. Dixon. Tracking and Regulation Control of a Skid Steering Vehicle. http://www.ornl.gov/~webworks/cppr/y2001/pres/119373.pdf
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