An automated radiographic NDT system for weld inspection: Part I — Weld extraction

An automated radiographic NDT system for weld inspection is developed. The entire system consists of two major components: weld extraction and flaw detection. Welds are first extracted from digitized radiographic images. The extracted welds are then processed by flaw detection algorithms to determine their qualities. This paper describes the weld extraction methodology, which forms the first part of the system. An example is used to illustrate the working of the methodology. The methodology is concluded to be effective for weld extraction after being successfully tested with 25 images.     

基于X射线数字化图像处理的双面焊焊缝缺陷检测

对双面焊焊缝的缺陷自动检测,提出了对焊缝重叠区边缘区与非边缘区分别进行处理、非细长缺陷与细长缺陷分别进行处理的思路.在逐列灰度波形分析检出焊缝外边缘和两焊缝重叠区边缘的基础上,对于非细长缺陷,采用大模版中值与均值滤波相结合模拟背景,然后对消除背景后图像采用分区域阈值检出焊缝缺陷,对于细长缺陷,提出了基于逐列自适应二值化和改进霍夫变换的缺陷分割算法.结果表明,所提出的方法能够在有效地避免两焊缝重叠区边缘处误检的同时,检出微弱线缺陷.     

Development of an automatic post-weld inspection system based on laser vision

In order to overcome the limitations of manual post-weld visual inspection approach, an automated inspection system is developed which uses three-dimensioual laser vision system based on the principle of optical triangulation. The system hardware consists of a modular development kit （MDK）, a computer, an actuating mechanism and so on. In image processing algorithms, extraction accuracy of centric line of laser stripe is the critical factor that determines the system performance. So according to the features of laser stripe image, a novel algorithm is developed to detect the central line of laser stripe fast and accurately. Experiments have demonstrated that this system can be used in various weld features inspection of both butt and fillet types of weld. Compared with traditional manual inspection method, this method has obvious dominance. The three-dimensional reconstruction result shows that this system has high accuracy and reliability.     

焊缝射线检测图像的缺陷搜寻与算法优化

基于X射线成像的焊缝缺陷自动检测技术对提高工业射线检测的自动化水平具有重要意义。在通过图像处理算法进行焊接缺陷提取的过程中,存在各种干扰,要求算法有很强的抗干扰能力。尝试了均值滤波背景相减和底帽变换两种缺陷提取算法,并分析存在的主要问题。针对这些问题,提出相应的解决办法,即模板优化算法和多特征再筛选算法,有效地解决了缺陷误检和漏检之间的矛盾。     

Development of an automatic weld surface appearance inspection system using machine vision

In this paper, an automatic inspection system for weld surface appearance using machine vision has been developed to recognize weld surface defects such as porosities, cracks, etc. It can replace conventional manual visual inspection method, which is tedious, time-consuming, subjective, experience-depended, and sometimes biased. The system consists of a CCD camera, a self-designed annular light source, a sensor controller, a frame grabbing card, a computer and so on. After acquiring weld surface appearance images using CCD, the images are preprocessed using median filtering and a series of image enhancement algorithms. Then a dynamic threshold and morphology algorithms are applied to segment defect object. Finally, defect features information is obtained by eight neighborhoods boundary chain code algorithm. Experimental results show that the developed system is capable of inspecting most surface defects such as porosities, cracks with high reliability and accuracy.     

计算机视觉焊缝识别技术研究

对焊缝识别技术进行了深入研究,包括对焊缝图像的中值滤波以降低噪声干扰、对图像的最佳阈值化以获取焊缝信息以及对图像的数学形态学处理以消除焊缝周围孤立点的干扰.在此基础上,提取到较为清晰的焊缝图像,进而采用最小二乘法建立焊缝的轨迹方程,为焊接控制提供依据,提高焊缝跟踪精度及焊接质量.     

X射线焊缝图像的缺陷检测与识别技术

针对目前无损检测主要采用人工方式存在的主观不一致、检测效率低、操作复杂等问题,设计了一套焊缝缺陷自动检测系统。提出基于Otsu双阈值分割的缺陷区域自动提取、图像的降噪和灰度增强的图像预处理方法;通过SUSAN算法检测焊缝缺陷目标,并结合形态学孔洞填充算法修正缺陷目标;计算焊缝缺陷目标特征参数,并结合所设计的深度为4的二叉树分类识别逻辑流程,实现了较好的焊缝缺陷的检测结果。     

超声波探伤在网架球接点焊缝缺陷检测中的应用

介绍了超声波探伤技术在检测网架球接点焊缝缺陷中存在的问题;通过对超声波探头、灵敏度专用标准当量试块和参考试块以及超声波探伤工艺等的改进,提高了球接点网架焊缝缺陷的检出率。     

一类窄焊缝的结构光图像特征提取方法

提出一种新颖的窄焊缝的特征提取与图像处理方法,有效地克服了环境的各种干扰,可靠地提取出了焊缝的特征点.首先设计了一套基于线结构光的显微视觉系统,可靠地检测出了结构光焊缝图像;接着提出一种基于阈值变换的行像素点统计算法和自适应形态学收缩算法可靠地分割出结构光条纹图像;然后采用过度参数直线拟合和B样条曲线拟合算法准确地得到了结构光条纹的中心线.最后,提出一种基于距离搜索的算法,得到了焊缝的特征点.结果表明,窄焊缝结构光图像特征提取方法可行.     

图像焊缝检测的圆形子窗口多步GPI方法

图像上紧密对接焊缝的提取是自动化焊接研究的难点.提出了焊缝检测新方法--圆形子窗口多步灰度投影积分(MSGPI)方法.在该方法中,利用圆形子窗口和灰度投影积分均值,克服了传统灰度投影积分(GPI)方法的缺陷;采用链表存储Sobel滤波所得边缘点,减少了计算量;用阈值法克服了划痕和锈迹干扰;利用划分角度区间分粗、精两步的检测措施,在保证精度的同时减少了计算量.结果表明,该方法能够快速准确地实现紧密对接焊缝的检测.     

高速SMT生产线自动视觉检测系统

利用自动视觉检测系统，实现对高速SMT生产线贴片质量的在线检测，详细介绍了视觉检测系统的LED光源，分析了使用此光源的优点，提出用两种灯光，分两次扫描PCB板，得到两幅图像，以增加图像的信息量，减少误判。经出图像采集的具体措施和图像处理的常用算法，并给出了应用算法的具体实例，此系统具有开放性，可根据实际需要增加算法，进一步降低误判。     

Automatic weld defect detection method based on Kalman filtering for real-time radiographic inspection of spiral pipe

A method based on Kalman filtering is proposed for weld defect detection in real-time radiographic NDT of spiral pipes. The existence of the image noises and the inhomogeneity of the background contrast induce numerous false alarms. In this paper, the trajectory continuity of the defects in the image sequence is detected by Kalman filtering for the identification of true defects. Potential defect regions without continuous motion are considered as false alarms and are eliminated. Experiments are performed to demonstrate the adaptability of the proposed method. The robustness of the method is also verified under unstable detection velocity.     

Weld seam recognition algorithm based on HSI space or pipeline ultrasonic flaw inspection

In order to realize automatic weld seam tracking for pipeline ultrasonic flaw inspection, an image processing algorithm based on HSI color space was presented. Since the color tones of weld seam were different from the parent metal, weld seam images were transformed to HSI color space. In the HSl colar space, the weld seam and base metal area can be apparently distinguished. By using this image processing algorithm, the edges and centerline of pipeline weld seam can be correctly extracted. An industrial application system was developed based on the image processing algorithm, and the image processing time is less than 70 ms and the accuracy of weld seam recognition is better than 2mm.     

基于图像色彩信息的焊缝识别算法

提出了基于图像色彩信息的焊缝识别算法,旨在为用于自动化焊接及自动无损检测的焊缝跟踪技术探索可能的解决方案.从色彩理论和图像分割的基本原理出发,开展了对RGB(红、绿、蓝)彩色空间中图像色彩信息表达的研究,提出了彩色空间变换的方法,根据灰度直方图对图像进行阈值分割,得到焊缝区与母材区基本被区分开的二值化图像,进而检出焊缝边缘.结果表明,该算法简便易行,识别效果好.     

铝合金焊缝图像的焊接区域提取与缺陷尺寸形状保真

针对焊缝图像的特点,探讨了焊接缺陷自动识别中焊接区域提取的问题,提出了三角拟合法焊道分割、焊道边界滤波修正等方法,并在此基础上,针对焊接缺陷尺寸与形状修正的问题,定义了缺陷矩形与终矩形的概念,设计了缺陷矩形生成策略、缺陷矩形的分割与生长循环、终矩形内缘提取等方法,在焊道区域提取、缺陷的尺寸与形状的保真方面取得了较好的效果。     

基于OpenMV的螺旋管内焊缝自动跟踪系统

针对国内部分钢材加工厂采用人工判断焊缝位置,手动调节来纠正焊偏的控制方式,自动化水平低且长时间工作导致视觉疲劳容易造成误判,影响螺旋管焊接质量的问题。该系统通过OpenMV机器视觉模块采集图像,利用图像处理技术实时提取焊缝特征信息,经过统计筛选来计算焊枪偏移量,结合控制技术来实现焊枪的自动纠偏。现场试验结果表明,该系统能够满足要求,稳定、准确的实现焊缝自动跟踪。     

基于信息融合优化搜索的X射线焊缝缺陷检测

提出一种基于信息融合优化搜索技术的X射线图像焊缝缺陷检测方法.在对X射线焊缝图像进行预处理的基础上,使用垂直焊缝方向投影的波形分析法进行焊缝区域分割,采用图像信息融合技术,综合不同判据获得启发式状态空间优化搜索的启发信息,对搜索过程进行优化,从而快速准确地检测出X射线图像中的缺陷区域.试验结果表明,提出的算法能够快速有效地检测出焊缝X射线图像中的缺陷,取得较好效果.     

焊缝轮廓线激光检测系统开发及算法实现

目前焊缝表面检测主要依靠肉眼观察和简单测量实现,其科学性、精确性受到检验人员主观因素的影响。线激光扫描方法是工业应用中比较先进的非接触轮廓检测方法。通过线激光扫描,利用激光三角测量法可以得到物体轮廓,进而得到物体的形貌信息。基于上述技术,开发了一套焊缝轮廓线激光检测系统,系统由半导体线激光器、CMOS工业相机、LabVIEW虚拟仪器软件平台组成。基于LabVIEW编写了包括图像采集、图像处理与焊缝轮廓计算的系统,能够得到较为准确的焊缝表面轮廓信息。     

拉深件缺陷在线检测系统设计

针对拉深缺陷人工检测的不足问题,提出了一种生产线上表面缺陷检测系统的设计方案。通过Halcon和VC++的联合开发,实现图像处理流程以及检测结果输出,包括摄像机标定、对图像进行平滑处理、利用动态阀值分割表面缺陷特征,通过形态学处理识别破裂缺陷,并对破裂缺陷分类和测量以及输出破裂缺陷外形和尺寸等,实现冲压生产线拉深件表面缺陷的自动检测功能。其中在相机标定过程中,采用Halcon的相机标定方法,快速获取图像坐标与世界三维坐标的对应关系,并实现缺陷特征的准确测量。此方案具有一定的稳定性,可提高检测效率。