CN105571502B - Measurement Method of Weld Gap in Friction Stir Welding - Google Patents
Measurement Method of Weld Gap in Friction Stir Welding Download PDFInfo
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Abstract
Description
技术领域technical field
本发明涉及视觉检测技术及搅拌摩擦焊接加工技术领域，具体地，涉及一种搅拌摩擦焊接中焊缝间隙的测量方法。The invention relates to the fields of visual detection technology and friction stir welding processing technology, in particular to a method for measuring weld seam gap in friction stir welding.
背景技术Background technique
搅拌摩擦焊接(FSW)作为一种固相连接技术，因具有成本低、焊接变形小、质量高、工期短等优点，成为航天领域贮箱制造过程焊接工艺的发展趋势。然而由于该技术的焊接特点，所允许的焊缝间隙和错边量均小于0.2mm，测量精度为±0.05mm，而且受搅拌头参数、焊接工艺参数选取不当等因素影响，难免会在焊接过程产生诸如孔洞、沟槽、未焊透、飞边以及Z线等焊接缺陷。为保证焊接质量，提高焊接设备对焊缝形状位置变化的适应能力及焊接控制的自动化水平，焊接前或焊接过程中必须对实际的焊缝形貌进行测量，从而降低焊接缺陷率，提高产品焊接品质。Friction stir welding (FSW), as a solid-phase joining technology, has become the development trend of the welding process in the manufacturing process of tanks in the aerospace field because of its advantages of low cost, small welding deformation, high quality, and short construction period. However, due to the welding characteristics of this technology, the allowable weld gap and misalignment are less than 0.2mm, and the measurement accuracy is ±0.05mm. In addition, due to factors such as stirring head parameters and improper selection of welding process parameters, it is inevitable that there will be some errors during the welding process. Welding defects such as holes, grooves, lack of penetration, flash, and Z-lines are generated. In order to ensure the welding quality, improve the adaptability of welding equipment to the change of weld shape and position and the automation level of welding control, the actual weld shape must be measured before welding or during welding, so as to reduce the welding defect rate and improve product welding. quality.
由于搅拌摩擦焊焊缝特征微小，测量精度要求高。目前，利用激光等光源与摄像机构成视觉传感系统，将激光投射到焊缝区域，CCD摄像机拍摄工件表面的图像并进行处理，可精确地获取物体表面三维信息的视觉测量技术已成为焊缝检测及跟踪的主要方法。由于搅拌摩擦焊焊缝特征微小，测量精度要求高。但已有的视觉检测产品大多只能检测焊缝间隙较大的特征，不适用于搅拌摩擦焊焊缝特征的检测。例如，型号为LJ-V7080的基恩仕激光测量仪，对不同大小的焊缝间隙进行多次重复性测量实验，发现该设备只在焊缝间隙大于0.7mm时，才能获得稳定的焊缝特征，且测量精度仅为±0.1mm。Due to the small characteristics of the friction stir welding seam, the measurement accuracy is required to be high. At present, a visual sensing system is formed by using a light source such as a laser and a camera. The laser is projected onto the weld area, and the CCD camera captures and processes the image on the surface of the workpiece. The visual measurement technology that can accurately obtain three-dimensional information on the surface of the object has become a weld inspection technology. And the main method of tracking. Due to the small characteristics of the friction stir welding seam, the measurement accuracy is required to be high. However, most of the existing visual inspection products can only detect the characteristics of large weld gaps, and are not suitable for the detection of friction stir welding weld characteristics. For example, the Keyence laser measuring instrument model LJ-V7080 has carried out repeated measurement experiments on weld gaps of different sizes, and found that the equipment can only obtain stable weld characteristics when the weld gap is greater than 0.7mm , and the measurement accuracy is only ±0.1mm.
发明内容Contents of the invention
针对现有技术中的缺陷，本发明的目的是提供一种搅拌摩擦焊接中焊缝间隙的测量方法，该方法能够在一个测量位置，实现焊缝间隙三维坐标和宽度信息的快速、精确和自动提取，从而得到焊缝的中心位置信息，为后续引导搅拌摩擦焊接过程奠定基础。Aiming at the defects in the prior art, the object of the present invention is to provide a method for measuring the weld gap in friction stir welding, which can realize fast, accurate and automatic measurement of the three-dimensional coordinates and width information of the weld gap at one measurement position Extraction, so as to obtain the center position information of the weld, and lay the foundation for the subsequent guidance of the friction stir welding process.
为实现以上目的，本发明提供一种搅拌摩擦焊接中焊缝间隙的测量方法，所述方法包括如下步骤：To achieve the above object, the present invention provides a method for measuring weld gap in friction stir welding, said method comprising the steps of:
S1、获取焊缝间隙区域的图像；S1. Obtain an image of the gap area of the weld seam;
S2、对S1得到的图像进行图像预处理，得到预处理后的激光条纹图像；S2. Perform image preprocessing on the image obtained in S1 to obtain a preprocessed laser stripe image;
S3、对S2得到的预处理后激光条纹图像利用边缘检测算法提取激光条纹的边缘信息；S3. Using an edge detection algorithm to extract the edge information of the laser stripe from the preprocessed laser stripe image obtained in S2;
S4、对S3得到的激光条纹边缘信息进行自适应感兴趣区域的选择；S4, performing adaptive selection of the region of interest on the edge information of the laser stripes obtained in S3;
S5、对S4得到的最终感兴趣区域利用改进重心法提取激光条纹的中心线；S5, using the improved center of gravity method to extract the centerline of the laser stripe from the final region of interest obtained in S4;
S6、通过S3得到的激光条纹边缘信息和S5得到的中心线信息得到焊缝间隙信息。S6. Obtain weld seam gap information through the laser stripe edge information obtained in S3 and the center line information obtained in S5.
优选地，所述的S1中：Preferably, in said S1:
采用线激光器投射出一个激光平面，与工件表面相交形成一条激光条纹，且激光条纹与焊缝间隙相交；CCD相机垂直安装于焊缝间隙的正上方，拍摄激光条纹图像。A laser plane is projected by a line laser, which intersects with the surface of the workpiece to form a laser stripe, and the laser stripe intersects the weld gap; a CCD camera is vertically installed directly above the weld gap to take images of the laser stripe.
优选地，所述的S2中：Preferably, in said S2:
对S1得到的激光条纹图像进行预处理，分别包括初始感兴趣区域的设定和自适应图像阈值分割，提高后续图像处理的效率和减少噪声干扰。The preprocessing of the laser stripe image obtained by S1 includes the setting of the initial region of interest and the adaptive image threshold segmentation, respectively, to improve the efficiency of subsequent image processing and reduce noise interference.
优选地，所述的S3中：Preferably, in said S3:
对S2得到的预处理后的激光条纹图像，采用Canny边缘检测算法进行边缘检测处理，提取激光条纹的边缘信息；包括二维高斯滤波处理、梯度计算、梯度的非极大抑制和连接边缘点。进一步，具体的：For the preprocessed laser stripe image obtained in S2, the Canny edge detection algorithm is used for edge detection processing to extract the edge information of the laser stripe; including two-dimensional Gaussian filter processing, gradient calculation, gradient non-maximum suppression and connecting edge points. Further, specifically:
首先、对S2得到的预处理后的激光条纹图像，进行卷积运算，以消除白噪声；First, perform convolution operation on the preprocessed laser stripe image obtained in S2 to eliminate white noise;
其次、对滤波后的图像中的每个像素点，通过一阶偏微分计算其梯度大小和方向；Secondly, for each pixel in the filtered image, calculate its gradient size and direction through the first-order partial differential;
再者、采用非极大抑制原理进行边缘检测，得到激光条纹的边缘点；Furthermore, the non-maximum suppression principle is used for edge detection to obtain the edge points of the laser stripes;
最后、连接边缘点。Finally, connect the edge points.
优选地，所述的S4中：Preferably, in said S4:
对S3得到的激光条纹边缘信息，查找该边缘的最小外接矩形，从而得到最终的感兴趣区域。For the laser stripe edge information obtained in S3, find the minimum circumscribed rectangle of the edge, so as to obtain the final region of interest.
优选地，所述的S5中：Preferably, in said S5:
在S4得到的最终感兴趣区域，采用改进重心法进行激光条纹中心的亚像素提取，包括粗略提取激光条纹中心、边界灰度阈值和精确的中心提取；进一步，具体的：In the final region of interest obtained in S4, the sub-pixel extraction of the center of the laser stripe is performed using the improved center of gravity method, including rough extraction of the center of the laser stripe, boundary gray threshold and precise center extraction; further, specifically:
首先、根据每列三个像素点的灰度值之和进行排序，选择灰度值之和最大的像素点位置作为粗略的激光条纹中心；First, sort according to the sum of the gray values of the three pixels in each column, and select the pixel position with the largest sum of gray values as the rough center of the laser stripe;
其次、计算每列像素点的灰度平均值，并将灰度值大于灰度平均值的像素点进行二次平均，作为边界灰度阈值，剔除小于边界灰度阈值的像素点；Secondly, calculate the average gray value of each column of pixels, and perform a second average on the pixels whose gray value is greater than the average gray value, as the boundary gray threshold, and remove the pixels smaller than the boundary gray threshold;
最后、以灰度值为权重，灰度值所在像素坐标为对应位置，实现激光条纹的精确提取。Finally, the gray value is used as the weight, and the pixel coordinates of the gray value are the corresponding positions to realize the precise extraction of laser stripes.
优选地，所述的S6中：Preferably, in said S6:
对S3和S5得到的激光条纹边缘信息和中心线，进行二维和三维视觉信息的有机融合，并对CCD相机、激光平面和运动状态进行标定，激光条纹中心线与激光条纹轮廓的交点即为焊缝间隙的边界，两焊缝间隙边界间的距离即为焊缝间隙的宽度，从而实现搅拌摩擦焊接过程中焊缝间隙的快速、精确、自动提取。The edge information and center line of the laser stripes obtained by S3 and S5 are organically fused with two-dimensional and three-dimensional visual information, and the CCD camera, laser plane and motion state are calibrated. The intersection point of the center line of the laser stripe and the outline of the laser stripe is The boundary of the weld gap, the distance between the two weld gap boundaries is the width of the weld gap, so as to realize the rapid, accurate and automatic extraction of the weld gap in the friction stir welding process.
与现有技术相比，本发明具有如下的有益效果：Compared with the prior art, the present invention has the following beneficial effects:
本发明所述方法能够在一个测量位置，实现焊缝间隙三维坐标和宽度信息的快速、精确和自动提取，从而得到焊缝的中心位置信息，为后续引导搅拌摩擦焊接过程奠定基础。The method of the invention can quickly, accurately and automatically extract the three-dimensional coordinates and width information of the weld gap at one measurement position, thereby obtaining the center position information of the weld and laying a foundation for the subsequent guidance of the friction stir welding process.
附图说明Description of drawings
通过阅读参照以下附图对非限制性实施例所作的详细描述，本发明的其它特征、目的和优点将会变得更明显：Other characteristics, objects and advantages of the present invention will become more apparent by reading the detailed description of non-limiting embodiments made with reference to the following drawings:
图1为本发明一实施例的方法流程图；Fig. 1 is a method flowchart of an embodiment of the present invention;
图2为本发明一实施例的焊缝测量装置结构示意图；Fig. 2 is a structural schematic diagram of a weld seam measuring device according to an embodiment of the present invention;
图3为本发明一实施例的焊缝区域原始数据示意图；Fig. 3 is a schematic diagram of the original data of the weld area according to an embodiment of the present invention;
图4a为本发明一实施例的图像预处理初始感兴趣区域示意图；Fig. 4a is a schematic diagram of an initial region of interest in image preprocessing according to an embodiment of the present invention;
图4b为本发明一实施例的图像预处理自适应图像阈值分割示意图；Fig. 4b is a schematic diagram of image preprocessing adaptive image threshold segmentation according to an embodiment of the present invention;
图5为本发明一实施例的边缘检测算法提取激光条纹边缘信息示意图；Fig. 5 is a schematic diagram of extracting edge information of laser stripes by an edge detection algorithm according to an embodiment of the present invention;
图6为本发明一实施例的自适应感兴趣区域选择示意图；FIG. 6 is a schematic diagram of adaptive ROI selection according to an embodiment of the present invention;
图7为本发明一实施例的改进重心法提取激光条纹中心线示意图；Fig. 7 is a schematic diagram of extracting the centerline of laser stripes by the improved center-of-gravity method according to an embodiment of the present invention;
图8为本发明一实施例的焊缝间隙的边界点示意图；Fig. 8 is a schematic diagram of boundary points of a weld gap according to an embodiment of the present invention;
图中：CCD相机1、镜头2、滤光片3、线光源激光4、待测工件5。In the figure: CCD camera 1, lens 2, optical filter 3, line light source laser 4, workpiece to be measured 5.
具体实施方式Detailed ways
下面结合具体实施例对本发明进行详细说明。以下实施例将有助于本领域的技术人员进一步理解本发明，但不以任何形式限制本发明。应当指出的是，对本领域的普通技术人员来说，在不脱离本发明构思的前提下，还可以做出若干变形和改进。这些都属于本发明的保护范围。The present invention will be described in detail below in conjunction with specific embodiments. The following examples will help those skilled in the art to further understand the present invention, but do not limit the present invention in any form. It should be noted that those skilled in the art can make several modifications and improvements without departing from the concept of the present invention. These all belong to the protection scope of the present invention.
如图1所示，本实施例提供一种搅拌摩擦焊接中焊缝间隙的测量方法，具体实施利用焊缝测量装置来进行，该实验装置包括CCD相机1、镜头2、滤光片3、线光源激光4和待测工件5，如图2所示。As shown in Figure 1, the present embodiment provides a method for measuring the weld gap in friction stir welding, and the specific implementation utilizes a weld seam measuring device to carry out, and the experimental device includes a CCD camera 1, a lens 2, an optical filter 3, a wire The light source laser 4 and the workpiece 5 to be measured are shown in FIG. 2 .
所述方法包括如下步骤：The method comprises the steps of:
S1、获取焊缝间隙区域的图像：S1. Obtain the image of the weld gap area:
采用线激光器投射出一个激光平面，与工件表面相交形成一条激光条纹，且激光条纹与焊缝间隙相交；CCD相机垂直安装于焊缝间隙的正上方，拍摄激光条纹图像。A laser plane is projected by a line laser, which intersects with the surface of the workpiece to form a laser stripe, and the laser stripe intersects the weld gap; a CCD camera is vertically installed directly above the weld gap to take images of the laser stripe.
将焊缝测量装置安装在五轴加工中心、待测工件5装夹在加工平台上；测量前对焊缝测量装置进行标定，标定包括CCD相机1的内外参数的标定、线光源激光器4激光平面方程的标定和焊缝测量装置与加工平台相对运动位置的标定；测量时，加工平台以630mm/min沿着X轴方向移动时，焊缝测量装置实时采集焊缝间隙区域的激光条纹图像，如图3所示，并传输至计算机。Install the weld seam measurement device on the five-axis machining center, clamp the workpiece 5 on the processing platform; calibrate the weld seam measurement device before measurement, including the calibration of the internal and external parameters of the CCD camera 1, and the laser plane of the line source laser 4 Calibration of the equation and calibration of the relative movement position between the weld seam measurement device and the processing platform; during measurement, when the processing platform moves along the X-axis direction at 630mm/min, the weld seam measurement device collects the laser stripe image of the weld gap area in real time, such as As shown in Figure 3, and transferred to the computer.
S2、对影像进行图像预处理：S2. Perform image preprocessing on the image:
①初始感兴趣区域的设定① Setting of the initial region of interest
将步骤S1得到的焊缝图像，设定初始感兴趣区域，在一实施例中，此处可以一共保留了30326个像素点，相比于原图像的1920000个像素点，极大地为后续图像处理提高了效率，如图4a所示；The weld seam image obtained in step S1 is used to set the initial region of interest. In one embodiment, a total of 30,326 pixels can be reserved here, which greatly facilitates subsequent image processing compared to the 1,920,000 pixels of the original image. Improved efficiency, as shown in Figure 4a;
②自适应图像阈值分割② Adaptive image threshold segmentation
如图3所示，激光条纹在焊缝间隙处断开，将浅色部分(即研究对象)称为图像亮域，深色部分(即焊缝表面实体)称为图像暗域；图像分割可以将图像分成若干个特定的区域(此处特定的区域是指根据图像处理所需的阈值范围，将图像亮域和图像暗域分割开)，并提取出感兴趣目标(图像亮域)；其中，图像阈值分割具有计算简单、运算效率较高、速度快的优点；而且实际应用中，图像的灰度值会因光照条件等因素发生相应的变化，则采用自适应阈值法得到清晰的测量目标，所谓的自适应阈值法是根据图像中最大灰度值和最小灰度值来决定的，并以经验值2/3作为影响因子来设定图像的阈值下 限，图像的阈值上限默认为255，从而实现图像亮域和图像暗域的分割，如图4b所示。As shown in Figure 3, the laser stripes are disconnected at the weld gap, and the light-colored part (that is, the research object) is called the bright region of the image, and the dark part (that is, the surface entity of the weld) is called the dark region of the image; the image segmentation can be Divide the image into several specific regions (the specific regions here refer to dividing the bright region of the image from the dark region of the image according to the threshold range required for image processing), and extract the target of interest (bright region of the image); where , the image threshold segmentation has the advantages of simple calculation, high computational efficiency, and fast speed; and in practical applications, the gray value of the image will change correspondingly due to factors such as lighting conditions, and the adaptive threshold method can be used to obtain a clear measurement target The so-called adaptive threshold method is determined according to the maximum gray value and the minimum gray value in the image, and the empirical value 2/3 is used as the influencing factor to set the lower threshold of the image. The upper threshold of the image is 255 by default. In this way, the segmentation of the bright region of the image and the dark region of the image is realized, as shown in FIG. 4b.
S3、利用边缘检测算法提取激光条纹的边缘信息：S3, using the edge detection algorithm to extract the edge information of the laser stripes:
对步骤S2得到的预处理后的激光条纹图像，采用Canny边缘检测算法进行边缘检测处理，提取激光条纹的边缘信息；具体包括：For the preprocessed laser stripe image obtained in step S2, use the Canny edge detection algorithm to perform edge detection processing, and extract the edge information of the laser stripe; specifically include:
①二维高斯滤波处理① Two-dimensional Gaussian filter processing
对步骤S2得到的图像进行卷积运算，消除白噪声；Carry out convolution operation to the image that step S2 obtains, eliminate white noise;
②梯度计算② Gradient calculation
对滤波后的图像中的每个像素点，通过一阶偏微分计算其梯度大小和方向；For each pixel in the filtered image, calculate its gradient magnitude and direction through a first-order partial differential;
③梯度的非极大抑制③ Non-maximum suppression of gradient
采用非极大抑制原理进行边缘检测，得到激光条纹的边缘点；Use the principle of non-maximum suppression for edge detection to obtain the edge points of the laser stripes;
④连接边缘点④ Connect edge points
根据上述阈值分割及滤波处理，并结合梯度的非极大抑制对图像边缘信息进行剔除和补充，将边缘信息点连接起来即可得到激光条纹轮廓，如图5所示；由图可见，激光条纹边界和焊缝边界显示为白色轮廓，其他信息屏蔽为黑色。According to the above-mentioned threshold segmentation and filtering processing, combined with non-maximum suppression of the gradient, the image edge information is eliminated and supplemented, and the edge information points are connected to obtain the laser fringe profile, as shown in Figure 5; it can be seen from the figure that the laser fringe Boundaries and weld boundaries are shown as white outlines, other information is masked in black.
S4、自适应感兴趣区域的选择：S4. Selection of adaptive region of interest:
对步骤S3得到的激光条纹边缘信息，查找该边缘的最小外接矩形，从而得到最终的感兴趣区域，极大地提高后续图像处理的效率，图6为自适应感兴趣区域。For the laser stripe edge information obtained in step S3, find the minimum circumscribed rectangle of the edge, so as to obtain the final region of interest, which greatly improves the efficiency of subsequent image processing. Figure 6 shows the adaptive region of interest.
S5、利用心法提取激光条纹的中心线：S5. Using the heart method to extract the centerline of the laser stripes:
在步骤S4得到的最终感兴趣区域中，采用重心法进行激光条纹中心的亚像素提取；具体包括：In the final region of interest obtained in step S4, the center of gravity method is used to extract the sub-pixel of the center of the laser stripe; specifically including:
①粗略提取激光条纹中心①Roughly extract the laser stripe center
根据每列三个像素点的灰度值之和进行排序，选择灰度值之和最大的像素点位置作为粗略的激光条纹中心；Sort according to the sum of the gray values of the three pixels in each column, and select the pixel position with the largest sum of gray values as the rough center of the laser stripe;
②边界灰度阈值②Boundary gray threshold
计算每列像素点的灰度平均值，并将灰度值大于灰度平均值的像素点进行二次平均，作为边界灰度阈值，剔除小于边界灰度阈值的像素点；Calculate the average gray value of each column of pixels, and double-average the pixels whose gray value is greater than the average gray value as the boundary gray threshold, and remove the pixels smaller than the boundary gray threshold;
③精确的中心点提取③Precise center point extraction
最后，以灰度值为权重、灰度值所在像素坐标为对应位置，实现激光条纹的精确提取，如图7所示。Finally, the weight of the gray value and the pixel coordinates of the gray value are used as the corresponding position to realize the precise extraction of laser stripes, as shown in Figure 7.
S6、通过激光条纹的轮廓和中心线信息得到焊缝间隙信息：S6. Obtain the weld seam gap information through the outline and centerline information of the laser stripes:
通过S3得到的激光条纹边缘信息(即激光条纹轮廓)和S5得到的激光条纹中心线，求两者交点即为焊缝间隙的边界点，如图8所示；根据测量前CCD相机1、线光源激光器4的激光平面和焊缝测量装置与加工平台相对运动位置的标定参数，运用三角测量原理，获得焊缝间隙边界点的三维坐标及间隙宽度。The edge information of the laser stripes (that is, the laser stripe profile) obtained by S3 and the center line of the laser stripes obtained by S5, the intersection point of the two is the boundary point of the weld gap, as shown in Figure 8; according to the CCD camera before measurement 1, line The calibration parameters of the laser plane of the light source laser 4 and the relative motion position of the weld seam measurement device and the processing platform are used to obtain the three-dimensional coordinates of the boundary points of the weld seam gap and the gap width by using the principle of triangulation.
本发明所述方法用于搅拌摩擦焊焊缝信息的在线提取，其中图像处理在OpenCV图像处理软件中进行，数据处理分析在C++软件系统中进行，并将特征信息在MFC界面中显示。The method of the present invention is used for on-line extraction of friction stir welding seam information, wherein the image processing is carried out in OpenCV image processing software, the data processing and analysis are carried out in the C++ software system, and the characteristic information is displayed in the MFC interface.
本发明所述方法能够在一个测量位置，实现焊缝间隙三维坐标和宽度信息的快速、精确和自动提取，从而得到焊缝的中心位置信息，为后续引导搅拌摩擦焊接过程奠定基础。The method of the invention can quickly, accurately and automatically extract the three-dimensional coordinates and width information of the weld gap at one measurement position, thereby obtaining the center position information of the weld and laying a foundation for the subsequent guidance of the friction stir welding process.
以上对本发明的具体实施例进行了描述。需要理解的是，本发明并不局限于上述特定实施方式，本领域技术人员可以在权利要求的范围内做出各种变形或修改，这并不影响本发明的实质内容。Specific embodiments of the present invention have been described above. It should be understood that the present invention is not limited to the specific embodiments described above, and those skilled in the art may make various changes or modifications within the scope of the claims, which do not affect the essence of the present invention.
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