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发动机油底壳涂胶控制与在线质量检测系统的研究
严长国
Subtype工学硕士
Thesis Advisor徐德
2016-05-16
Degree Grantor中国科学院大学
Place of Conferral北京
Keyword缺陷定位 宽度测量 运动规划 视觉检测 机器人 自动涂胶
Abstract       自动涂胶是发动机装配中的重要环节,高效可靠的涂胶系统保障了发动机润滑系统的长期稳 定工作。本文以发动机油底壳适配器自动涂胶为背景,对机器人涂胶的运动控制方法和胶线质量的视觉检测技术开展了研究。本文采用的涂胶机器人为直角坐标式的3自由度机器人,其中1个自由度用于抬起与放下胶枪,2个自由度用于控制涂胶轨迹。构建的视觉系统采用两台高分辨率摄像机,分别采集油底壳适配器左右半区的图像。
       针对涂胶轨迹需要绕过螺纹孔的特点,提出了基于连续多圆弧过渡的直线轨迹规划方法。该方法利用多段圆弧实现螺纹孔两侧的两段直线之间的平滑连接,可以根据螺纹孔位置及过渡圆弧的半径自动生成圆弧关键点坐标,从而获得油底壳适配器涂胶面上的连续平滑的完整涂胶轨迹,为实现机器人平滑涂胶提供了保障。
       针对供胶系统在打开阀门的瞬间出现的“喷胶”现象,提出了基于速度补偿的胶量控制方法。该方法利用匀速涂胶过程的涂胶结果,建立了简单的供胶系统的时间-胶量模型。根据该模型推导出在期望胶线宽度下的涂胶时间-速度函数,根据速度规划的要求,并结合时间-位置关系得到速度规划所需要的位置-速度曲线,改善了涂胶初始阶段的胶线均匀性。
       针对胶线中心线提取过程中出现的毛刺问题,设计了基于最长路径的消除毛刺算法。基于胶线中心线为细化结果中的最长路径这一先验知识,该算法通过一次扫描建立了细化结果的树状拓扑结构,将最长路径问题转化为两个最优子问题,采用递归方法得到从细化结果中提取中心线。该算法在彻底消除毛刺的过程中保证了中心线的结构不受到破坏,适用于线状对象的中心线提取。
       针对胶线宽度测量的问题,提出了基于胶线中心线和外轮廓的宽度测量方法。该方法借鉴人的测量习惯,在中心线上采样测量点,使用局部抛物线拟合中心线和外轮廓,通过求解中心线法线与轮廓拟合曲线的两个交点间的距离来测量胶线的宽度。
       在实际的油底壳适配器涂胶系统中,对上述方法和算法进行了实验验证,实验结果表明了上述方法和算法的有效性。
Other Abstract      Automatic gluing is a key step of the engine assembly. The high efficient, reliable sealant coating system leads to the sustainable running of the engine lubrication system. In this paper, based on the automatic gluing for engine oil pan’s adapter, our research is focused on the gluing robot’s control technology and vision inspection technology for the glue line’s quality. The Cartesian robot used in this paper has 3 degrees of freedom (DOF). One DOF is applied to put up/down the glue gun and the other DOFs control the glue gun to move along the trajectory. The vision system is composed of two cameras with high resolution. Each of the cameras captures the image of half part of the engine oil pan’s adapter.
        Considering that the gluing trajectory needs to bypass the screw holes, the straight line trajectory planning method based on the continuous multi-arc transition is proposed. This method achieves the smooth connection of the straight trajectories on both sides of the screw hole by using multiple arcs. And this method is able to automatically calculate the key points’ coordinates according to the screw hole’s position and the radius of the transitional arcs. With those key points’ coordinates, the complete, continuous and smooth gluing trajectory could be easily obtained, which guarantees the gluing’s smoothness.
      Aiming to the spewing phenomenon of sealant appearing in the beginning of gluing, a sealant flow control method by adjusting the gluing speed is proposed. The time-flow model is built by using the gluing result at a constant speed. According to the model, time-gluing speed model is given for any given expected sealant line’s width. Finally, in order to plan the gluing speed in position space, the two models above are combined to get the position-gluing speed model. This method could refine the uniformity of the glue line.
      A fast and novel algorithm is proposed to remove the burrs based on the longest path in the thinning image. Due to the prior knowledge that the centerline is always the longest path in the thinning image, the tree-form topological structure is established by scanning once the image. Then the longest path problem can be converted into two small problems. Both of the problems have the optimal substructures and could be recursively solved. This algorithm is able to remove all burrs thoroughly in the thinning image and keep the centerline unbroken. This algorithm could also be extended to the centerline extraction of other ribbon-like objects.
      A centerline and contour based width measuring method for the sealant line is proposed, which makes use of the human’s measuring habits for reference. The measuring points are got by down sampling the centerline. Following are the partial fitting of parabola for the centerline and two contours segments. The width is obtained by calculating the distance of two intersections of centerline’s normal and fitted contours.
      The methods and algorithms are tested by the experiments on the gluing system and the results showed the efficiency of them.
Language中文
Document Type学位论文
Identifierhttp://ir.ia.ac.cn/handle/173211/11531
Collection毕业生_硕士学位论文
Affiliation中国科学院自动化研究所
Recommended Citation
GB/T 7714
严长国. 发动机油底壳涂胶控制与在线质量检测系统的研究[D]. 北京. 中国科学院大学,2016.
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