对接接头焊件批量缺陷空间位置的可视化

创建了对接接头焊件缺陷深度和偏移量的数学模型,确定了缺陷的空间位置.提出了对接接头焊缝轮廓线数学模型,实现了焊缝轮廓线的完美呈现.设计了对接接头焊件缺陷可视化界面,创建了对接接头焊件模型,导入了自动提取的对接接头焊件批量缺陷,实现了对接接头焊件批量缺陷的空间位置再现.介绍了焊件参数调整、可视角度调节和透明化设置等功能及实现方法,展示了可视化模型的三视图,可为对接接头焊件缺陷修补、焊接工艺制订、缺陷空间分布特征研究和结构完整性评价奠定良好基础.     

多腹板焊件批量缺陷的空间位置可视化

在创建单腹板焊件三维模型的基础上,采用线性变换的方法对焊件中的焊缝缺陷进行了空间坐标转换,并构建了多腹板焊件的三维模型。创建了交互性良好的可视化界面,导入已提取的焊件缺陷空间位置数据,实现了多腹板焊件缺陷的空间位置可视化,并大大提高了缺陷可视化的效率。开发的可视化程序具有如下功能:焊件模型尺寸修改、模型自动生成、透明化调整、视角变换、自动旋转、任意位置观察、多腹板焊件正反面焊缝批量缺陷同时可视化等,为该类焊件无损检测及结构完整性评价奠定了良好的研究基础,也可为同类焊件内部缺陷的可视化提供有价值的参考,工程应用前景广阔。     

双面T形焊件中批量缺陷空间定位数据的自动提取

提出了双面T形焊件中小缺陷的空间位置数据自动提取算法.该算法主要由两部分组成:一是自动提取投影距离和缺陷距焊缝上端的距离,二是自动提取缺陷尺寸和缺陷距焊缝上端的距离.设计了双面T形焊件左右旋转图像中缺陷的自动对应准则,实现了其内部小缺陷空间位置数据的快速提取.采用实际焊件破坏性试验的方法对上述算法进行了验证.结果表明,文中提出的算法是可行的.     

工字形焊件射线图像中铸造缺陷的去除方法

为了消除腹板中铸造缺陷对焊缝缺陷空间定位、空间位置数据自动提取及空间位置可视化的干扰,本文在分析工字形焊件检测图像特点的基础上,提出了一种去除铸造缺陷的新算法。该算法分为两个步骤:①首先在分割图像中逐行搜索腹板区与焊缝区交界点的位置,从而确定腹板区的大小;②在已确定的腹板区逐行搜索铸造缺陷,如发现白点则置其为黑点,进而实现铸造缺陷的去除。对多幅图像的处理结果表明,算法可适应不同高度腹板的处理需求,且算法鲁棒性强。因去除铸造缺陷的处理仅在腹板区进行,可大大提高图像处理的速度。铸造缺陷去除算法的实现为后续的焊缝缺陷空间定位、空间位置数据自动提取等奠定了良好的基础,具有重要的实际意义。     

工字形焊件中批量缺陷的自动对应准则

为了实现工字形焊件中批量缺陷空间位置数据的自动提取,在缺陷分割与细化的基础上提出了批量缺陷的自动对应准则,探讨了影响缺陷自动对应判定的因素.应用提出的自动对应准则对实际焊件进行了批量缺陷空间位置数据的自动提取,并与手工对应的结果进行了对比.结果表明,采用文中算法对应到的缺陷与手工检测结果基本一致,但检测效率却大幅度提高,并大大减轻了检测人员的劳动强度,为该焊件的快速无损检测及接头完整性评价奠定了良好的基础.     

双面T形焊件中单侧投影重合缺陷的自动判别方法

为了实现双面T形焊件中单侧投影重合缺陷空间位置数据的自动提取，在原有自动判别准则的基础上提出了单侧投影重合缺陷的自动判别方法. 该方法首先对焊件左转或右转射线检测图像进行逐行搜索，通过采用缺陷中心点距图像上端距离相同的方法找出单侧投影重合的缺陷，然后通过对比单侧投影重合缺陷的左右投影距离，判别重合缺陷在焊件内部的深度位置，从而将重合缺陷区分出来. 采用提出的方法对实际焊件中的单侧投影重合缺陷进行了自动判别，试验结果表明提出的方法是可行的.     

复杂结构中焊接缺陷的空间分布特征

采用X射线实时成像方法对复杂结构钛合金激光焊件进行了无损检测,并基于缺陷位置的线灰度分布曲线确定了焊件中微小缺陷的空间位置,推导出了一个计算缺陷埋藏深度的公式。针对峰值异常和斜凹形异常缺陷分别提出了一个缺陷到射线穿透焊件最薄处的投影距离自动提取算法。试验结果表明,上述算法能很好地计算出投影距离并进而确定缺陷空间分布特征。     

工字型焊件中批量小缺陷的空间位置可视化

开发了基于Matlab的焊件缺陷可视化软件,详细阐述了焊件三维建模、缺陷数据自动输入、缺陷自动显示、透明化处理和旋转角度调整等功能的创建过程。另外还设计了GUI界面,大大提高了缺陷的可视化效率。该可视化程序的开发把激光焊件的缺陷检测、分割、空间定位与空间位置可视化连接成一个有机的整体,可为实际的焊接接头检测和结构完整性评价提供有价值的参考信息。     

工字形激光焊件中批量缺陷定位数据的自动提取

为了确定工字形焊件中批量缺陷的空间位置,采用多视角几何的方法对其进行了无损检测.提出了工字形激光焊件中小缺陷的深度与偏移量计算的数学模型,确定了精密焊缝中小缺陷的深度和偏移量.对影响缺陷定位精度的因素进行了理论分析,得出了影响缺陷定位精度的主要因素.为了实现焊件的快速检测和提高检测的鲁棒性,在缺陷分割与细化的基础上提出了缺陷投影距离自动提取的算法,并采用模拟缺陷的方法对上述算法进行了验证.结果表明,该方法是可行的.     

钢箱梁桥焊缝的超声波探伤

随着我国交通运输业的快速发展,高速公路和铁路上的钢制桥梁越来越多(如昆明-安宁高速公路上使用了较多跨度很大的钢箱梁桥)。按照图纸技术条件及规范要求,钢箱梁桥构件的腹板、顶板、底板的拼接为全熔透对接焊缝,腹板与顶板、底板的连接为全熔透角焊缝。对需要焊透的焊缝按技术条件及规范要求进行超声波探伤,以确保焊缝内不存在未焊透等缺陷,从而保证钢箱梁桥的焊接质量。1超声波检测方案钢箱梁桥材质一般为Q345q(D)钢,腹板厚度为12~20 mm,顶板、底板厚度为14~20 mm,钢箱梁桥跨度长为35~50 m,焊缝多用二氧化碳气体保护焊,一般角焊缝焊脚尺寸为hf=0.7t(t为腹板厚度),对接焊缝余高≤4.0 mm。气孔和夹渣是体积型缺陷,只要不超标,危害性较小,而裂纹、未焊透和未熔合是平面型缺陷,在运行中容易发展扩大,危害性较大,是绝对不允许存在的。钢箱梁桥的全熔透角焊缝是T形接头,腹板厚12 mm,钢箱梁内侧开V形坡口;腹板厚14 mm以上钢箱梁开K形坡口,不留钝边,根部留3 mm间隙,先焊内侧,外侧碳刨清根。根据钢箱梁桥设计图纸、技术规范及JTJ041—2000《公路桥涵施工技术规范》标准要求,各种构件焊缝质量等级及缺...     

Automatic extraction and visualization of spatial position data for bulk porosities in laser weldments with complex structures

The left and right-turning scheme of weldments was adopted to detect small porosities in laser weldments with complex structures. Detection images were obtained in this study. An algorithm that determines the optimal structure elements for morphology simulation was provided to achieve fidelity segmentation of small porosities. Mathematical models for the defect depth and deviation of bulk porosities were established based on the geometric features of laser weldments. Thus, the features of spatial distribution of small porosities were determined. To improve detection efficiency, the automatic extraction of spatial position data for bulk porosities was divided into two parts: automatic extraction of projection distance, which is important for the determination of weld porosity depth and deviation, and automatic extraction of porosity size. The porosity distribution in the longitudinal direction was obtained by automatic searching, and the features of the spatial distribution of weld porosities were procured. A 3D model of laser weldments was established to visualize the spatial distribution of porosities. Extracted data were inputted to the model, and the spatial positions of bulk porosities were visualized.     

Research on segmentation and distribution features of small defects in precision weldments with complex structure

In order to study the segmentation and quantitative problem of small defects in precision weldments with complex structure, an automated image processing system was setup based on the Visual Basic 6.0 development environment. The weld zones were extracted by adopting the method of twice automatic threshold, and the small defects were segmented successfully by using sharpen, smoothing processing and background subtraction in the extracted weld zones. To determine the spatial distribution features of small defects, calculation formula of defects depth and deviation were deduced individually, and the projection distance of small defects can be extracted automatically also. The image processing system can achieve the goal of small defects segmentation and automatic extraction of projection distance. The depth and deviation of small defects can be obtained through the above deduced formula, and the longitudinal distribution of small defects can be obtained from the detection image, then the spatial distribution features of small defects can be determined.     

Image segmentation of small defects in precision weldments with complex structure

In this paper, the X-ray nondestructive test method of small defects in precision weldments with complex structure was presented. To resolve the difficulty of defect segmentation in variable grey image, the image processing based on Visual Basic programming method was adopted. The methods of automatic contrast and partial grey stretch were used to enhance the X-ray detection image which has relatively low contrast, then automatic threshold method was carried out to segment the two high intensity zones, and weld zones which contain the small defects was extracted. Smoothing and sharpen processing were proceeded on the extracted weld zones, and small defects in X-ray detection image of weldments with complex structure were segmented by using the method of background subtraction in the end. The effects of raster were eliminated, and because of that the image processing was only proceeded on the extracted weld zones, the calculated speed using the above provided algorithm was improved.     

微间隙焊缝磁光检测神经网络修正

针对激光焊接微间隙焊缝（间隙小于0.1 mm）,研究提高磁光传感检测焊缝精度的BP神经网络修正方法.以碳钢平板对接激光焊为试验对象,利用磁光传感器检测焊缝区域磁场分布并成像.通过分析焊缝处磁场成像并应用BP神经网络修正磁光传感器得到焊缝中心数据,有效避免焊缝磁光图像低对比度和强噪声干扰问题.经过在不同焊接速度试验下的测试,四组神经网络试验的焊缝位置误差的绝对平均值都在0.015 mm左右,BP神经网络测量误差比磁光成像直接测量平均减少约28%.BP神经网络修正磁光成像测量技术可有效识别微间隙焊缝,为解决激光焊接微间隙焊缝过程自动识别和跟踪焊缝的难题提供了一种新方法.     

微间隙焊缝磁光成像小波多尺度融合检测

针对微间隙(小于0.1 mm)对接焊缝,通过对焊件施加感应磁场,并利用法拉第旋光原理构成的磁光传感器,获取焊缝磁光图像.为了获取焊缝的准确位置,研究一种焊缝磁光图像的小波多尺度信息融合边缘检测方法.对焊缝磁光图像进行3层小波分解,获得包含焊缝边缘信息的小波高频图像.根据各尺度高频信息包含的细节丰富度,融合各尺度高频图像,然后用小波模局部极大值对融合图像进行边缘检测,得到抗噪性和连续性好、定位精度高的焊缝边缘,最后进行焊缝跟踪试验.结果表明,磁光图像小波多尺度信息融合是一种有效的焊缝边缘提取方法,适用于磁光成像传感的微间隙焊缝跟踪图像处理过程.     

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。