共查询到19条相似文献,搜索用时 140 毫秒
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在激光拼焊中,背面焊缝成形质量直接影响焊件的机械性能.文中在分析结构光视觉检测原理的基础上,建立了基于结构光视觉传感的焊后焊缝背面质量检测系统并对焊缝背面质量检测系统图像处理方法进行了深入研究.在图像处理过程中,首先通过开窗处理来获得兴趣区域,采用中值滤波去除图像噪声;其次使用迭代自动阈值法分割出结构光;在结构光条纹中心线提取过程中,提出了一种新的模板法获得了条纹的边界并用几何中心法提取了条纹中心线;然后,将斜率分析法引入到条纹中心线特征点检测中并获得了中心线上的一系列特征点.最后通过背面焊缝的图像序列,计算获得了背面焊缝不同位置处的几何参数及缺陷值.试验表明,该焊缝背面质量检测系统图像处理方法可靠性高、运算速度快、抗干扰能力强,具有较高实用价值. 相似文献
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基于视觉的激光拼焊焊缝表面质量在线实时检测系统中,结构光条纹中心线能否快速、准确提取是影响检测系统性能的关键因素之一。传统的高斯拟合法和Hessian矩阵法虽然具有较高的亚像素提取精度,但其计算量非常大,无法满足实时性的要求。文中在分析激光拼焊焊缝质量检测系统中结构光条纹图像特点的基础上,将传统的几何中心法引入到结构光条纹中心线提取中,提出了一种精度介于像素级到亚像素级之间的局部阈值几何中心法。实验表明:该算法具有较高的精度和较强的抗干扰能力,实现了视觉检测系统中结构光条纹中心线的快速提取,为激光拼焊焊缝质量视觉检测系统在线实时检测奠定了基础。 相似文献
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焊缝质量自动检测是实现焊接自动化的关键技术。文中在分析结构光视觉检测原理的基础上,建立了基于结构光视觉的激光拼焊焊缝质量检测系统并对检测系统的图像处理方法进行了研究。对原始图像进行了开窗处理和中值滤波,并使用迭代阈值法获得了结构光光纹。提出了一种简化的模板获得了光纹的边界点并使用几何中心法提取了光纹中心线。使用平均斜率法识别出光纹中心线的特征点。分析了激光拼焊焊缝截面轮廓的特点并建立了截面轮廓几何参数计算方法。实验结果表明该检测系统可以完成焊缝截面轮廓相关参数的计算。 相似文献
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针对结构光条纹曲率变化较大时中心线提取存在误差,导致焊后角焊缝外观参数检测不准确的问题,提出一种基于结构光的角焊缝外观检测算法。首先建立角焊缝外观检测系统并对系统内相机进行标定;然后采集图像并经过高斯滤波、Otsu值分割等一系列图像预处理,提出一种法向平均法来提取结构光条纹中心线;最后通过直线拟合法与移动向量法来提取结构光特征点,结合角焊缝外观定义计算出其宽度、凸度和咬边等外观参数。实验结果表明,所提出的角焊缝外观检测算法准确性高,平均误差为0.021mm,且系统算法具有良好的稳定性。 相似文献
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针对V型坡口中厚板对接焊焊接过程中存在的系统噪声和测量噪声的问题,采用了斜率分析与卡尔曼滤波相结合的方法进行了焊缝跟踪。使用激光视觉传感系统采集了V型坡口的条纹图像,获取了测量系统内外标定参数,通过锯齿靶标建立了焊缝特征点坐标转换模型;提出了一种基于极值法的边界约束灰度平方加权重心法,提取出了激光条纹线的中心点,采用斜率分析法寻找到了激光条纹中心线拐点,对每一段条纹中心线通过最小二乘法拟合求交,提取出了焊缝特征点;利用卡尔曼滤波方法对系统噪声和测量噪声进行了优化;对V型坡口进行了厚板对接焊试验,焊炬能始终对准焊缝中心。研究结果表明:基于斜率分析法与卡尔曼滤波的焊缝跟踪方法能够减小系统噪声干扰的影响,实现了焊缝特征点的准确提取,提高了焊缝跟踪精度。 相似文献
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基于物理模型的计算机视觉轮对踏面擦伤检测方法 总被引:3,自引:1,他引:2
研究一种基于计算机视觉的轮对踏面擦伤检测方法.用线结构光扫描轮对踏面,在踏面上产生相应的变形光条纹,利用电荷耦合器件(Charge coupled device,CCD)摄像机采集光条纹图像,经过图像处理后获得踏面截面轮廓,检测轮对踏面擦伤.根据光条纹的特点,提出基于物理模型的提取光条纹中心线方法,应用能量优化法,求解光条纹中心线所对应的最小能量曲线,用B样条曲线拟合光条纹中心线使其具有亚像素级定位精度,同时大大减少数据存储量.试验结果表明该方法可有效地抑制噪声、光条纹断线及分枝的影响,使光条纹中心线具有单一连通性.轮对旋转一周,通过摄像机模型计算轮对踏面的三维曲面模型,实现了轮对踏面擦伤的非接触精确检测. 相似文献
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针对V型坡口中厚板对接焊焊缝特征点检测精度不高的问题,研究了一种基于激光视觉传感的角点检测与光流(LK)跟踪的焊缝特征快速提取与定位方法。根据三角测量原理,设计了能够实时检测焊缝特征图像的激光视觉传感器,并建立了由激光条纹特征点像素坐标到焊缝特征点三维坐标的数学模型;对焊缝图像进行了预处理,采用Shi-Tomasi角点检测提取了焊缝特征;最后使用光流法为后续帧匹配特征角点,实时计算出了图像中焊缝特征点的亚像素位置。研究结果表明:基于角点检测与光流法跟踪的焊缝特征提取与定位方法,其特征点检测精度较高,平均误差在±0.13 mm以内,可以实时、准确地识别焊缝特征。 相似文献
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随着焊接过程自动化和智能化的发展,基于图像处理技术的焊缝位置检测和焊接缺陷检测过程越来越受到国内外学者的重视。本文对焊缝自动跟踪系统中有关图像处理方面的内容作了分析。详细分析了图像处理技术在焊缝跟踪过程中的应用,其中包括图像预处理,边缘检测和特征点提取等图像处理过程;并对当前焊缝跟踪中的图像处理技术存在的问题和解决方法作了一些总结和分析,最后对其应用前景作了展望。 相似文献
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Haiyong Chen Kun Liu Guansheng Xing Yan Dong Hexu Sun Wei Lin 《The International Journal of Advanced Manufacturing Technology》2014,71(9-12):1849-1860
In this paper, an image-based visual servo control system is developed and integrated into a double head welding robot for CO2 gas shielded arc welding, which is mainly used to weld the narrow seam whose width is generally less than 0.2 mm. Firstly, a robust and reliable image processing algorithm is presented to reliably extract the seam feature during the welding. A statistic-based filter method is proposed to effectively weaken the image noises caused by various disturbances. The region of interest (ROI) of the image is determined to improve the efficiency and reliability of the image processing. The feature line of the narrow seam is extracted by combining the technique of the least-square line fitting with the Hough transform method. Secondly, a visual servo control system is designed to realize accurate tracking and initial point localization of the narrow seam. Moreover, an image error filter and output pulse verification are utilized to guarantee the reliability and stability of the control system. Finally, a series of experiments with real welding robots are conducted in the production line of a container manufacturing factory, demonstrating the satisfactory performance and high welding quality of the proposed visual servo control system. 相似文献
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Development of a real-time laser-based machine vision system to monitor and control welding processes 总被引:2,自引:2,他引:0
Wei Huang Radovan Kovacevic 《The International Journal of Advanced Manufacturing Technology》2012,63(1-4):235-248
In this study, a laser-based machine vision system is developed and implemented to monitor and control welding processes. The system consists of three main modules: a laser-based vision sensor module, an image processing module, and a multi-axis motion control module. The laser-based vision sensor is designed and fabricated based on the principle of laser triangulation. By developing and implementing a new image processing algorithm on the platform of LabVIEW, the image processing module is capable of processing the images captured by the vision sensor, identifying the different types of weld joints, and detecting the feature points. Based on the detected feature points, the position information and geometrical features of the weld joint such as its depth, width, plates mismatch, and cross-sectional area can be obtained and monitored in real time. Meanwhile, by feeding these data into the multi-axis motion control module, a non-contact seam tracking is achieved by adaptively adjusting the position of the welding torch with respect to the depth and width variations of the weld joint. A 3D profile of the weld joint is also obtained in real time for the purposes of in-process weld joint monitoring and post-weld quality inspection. The results indicate that the developed laser-based machine vision system can be well suited for the measurement of weld joint geometrical features, seam tracking, and 3D profiling. 相似文献
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Markus Heber Martin Lenz Matthias Rüther Horst Bischof Hartwig Fronthaler Gerardus Croonen 《The International Journal of Advanced Manufacturing Technology》2013,65(9-12):1371-1382
Traditionally, automated quality inspection of welding tasks relies on nonvisual information and is mainly done off-line. In this work, we introduce an image acquisition system which is capable of monitoring the welding process on-line, resulting in high-quality image information during an ongoing welding process. We show how to further exploit this image information by automatically tracking the weld seam position in the image, even under heavy smoke and gas disturbances. We exploit the high information redundancy between subsequent frames given by large overlap to generate a seamless image of the entire weld seam and effectively suppress adverse optical effects caused by, e.g., smoke and sparks. 相似文献
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随着焊接过程自动化和智能化的发展,图像处理技术越来越受到国内外学者的重视,它在焊缝自动跟踪系统中也有广泛的应用。本文介绍了图像处理的基本过程,其中包括图像预处理,图像分割,边缘检测和特征点提取等图像处理过程,总结了一些传统和新型的图像处理算法,并着重分析了焊缝中心提取的几种方法,提出了一种求取平均值的简单有效的方法。 相似文献
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Yanling Xu Gu Fang Shanben Chen Ju Jia Zou Zhen Ye 《The International Journal of Advanced Manufacturing Technology》2014,73(9-12):1413-1425
Image capturing and processing is important in using vision sensor to effectively track the weld seam and control the weld quality in robotic gas metal arc welding (GMAW). Using vision techniques to track weld seam, the key is to acquire clear weld images and process them accurately. In this paper, a method for real-time image capturing and processing is presented for the application in robotic seam tracking. By analyzing the characteristic of robotic GMAW, the real-time weld images are captured clearly by the passive vision sensor. Utilizing the main characteristics of the gray gradient in the weld image, a new improved Canny edge detection algorithm was proposed to detect the edges of weld image and extract the seam and pool characteristic parameters. The image processing precision was further verified by using the random welding experiments. Results showed that the precision range of the image processing can be controlled to be within ±0.3 mm in robotic GMAW, which can meet the requirement of real-time seam tracking. 相似文献
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采用微型排水罩的药H焊丝水下焊接焊缝自动跟踪系统 总被引:2,自引:0,他引:2
针对水下焊接图像噪声大、清晰度差的特殊情况,设计并研制成功一套药芯焊丝水下焊接的视觉传感焊缝自动跟踪系统.该系统由视觉传感、图像预处理及偏差识别系统,控制系统和执行机构等组成.采用小波多尺度变换进行水下焊缝图像边缘提取,结果保留大多数的细节,得到有利于焊缝位置特征提取的预处理图像,在一种基于二值图像的焊缝中心位置识别算法计算后,得出焊缝偏差.在理论分析视觉传感焊缝自动跟踪系统模型的基础上,设计满足跟踪精度要求的规则自调整模糊算法.对影响跟踪系统精度的因素进行分析,并采用相应的措施以提高系统的精度.通过药芯焊丝湿法水下焊接焊缝自动跟踪试验表明,采用规则自调整模糊控制能够达到较高的焊缝跟踪精度.在斜线、折线和曲线三种不同形状待焊焊缝的跟踪试验中,系统都能满足药芯焊丝水下自动焊接的要求.经过改进微型排水罩,进行微型排水罩局部干法药芯焊丝水下焊接焊缝跟踪试验,采用规则自调整模糊控制,不仅得到满意的焊缝跟踪效果,还改善焊缝成形质量. 相似文献