基于机器视觉的管端矫圆几何特征识别系统研究
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摘要
自从河北青县巨龙钢管有限公司引进了我国第一条大口径直缝埋弧焊管JCO生产线后,我国开始对管坯JCO成形工艺及相关技术进行了消化及吸收,由于关键技术和设备从国外引进,对管坯成形质量控制及工艺参数调整仅停留在经验层面上,存在着工艺参数调整误差大、人员工作强度大及产品质量波动大等现实情况。为此,本文提出了大口径直缝埋弧焊管JCO成形后管端几何特征识别技术,以实现管端成形质量的检测。
本文在板材弯曲智能化控制技术的研究成果基础上,对基于机器视觉的管端矫圆几何特征识别系统的关键问题进行解决。
利用机器视觉和传感器技术,开发了基于机器视觉的管端矫圆几何特征识别系统,实现了管端几何特征参数的非接触、高精度的测量。详细研究了管坯端面图像处理和椭圆检测算法,在试验和结果比较基础上,提出了适合管坯端面的图像处理流程。本文用了适合现场使用的正三角形标定方法。
在上述研究基础上,利用Visual C++编程语言开发了基于机器视觉的管端矫圆几何特征识别系统软件,主要包括:管坯端面图像处理及椭圆检测、拟合的程序开发。最后利用PCI总线数据采集卡、面阵CCD及相关硬件,完成了基于机器视觉的管端矫圆的几何特征识别的硬件系统开发。
利用基于机器视觉的管端矫圆几何特征识别系统进行了物理模拟实验,实验结果表明系统运行稳定,检测精度高。方便和高精度的管端几何形状测量是研究工作的最终成果。
Since the first longitudinal-seam submerged arc welded (LSAW) pipes production line with JCO forming process was established in Julong Steel Pipe Co., Ltd, the unfinished pipe forming process and the correlated technology have been investigated by the researchers. Due to the key technology and the forming press from abroad, the systematical basic research on the forming process has not been conducted yet. And the pipe quality and processing parameters adjustment are conducted according to accumulated experience with the characteristics of large error, high personnel working strength and unstable production quality. As one of the effective method to improve the pipe-end quality, the technology of geometric feature recognition of the pipe-end is introduced to detect the pipe quality.
Based on the research achievements of the intelligent control technology for the sheet metal bending, the key issue of the geometric feature recognition system of correcting pipe-end based on machine vision is resolved in this paper.
Based on machine vision and sensor technology, the geometric feature recognition system of correcting pipe-end based on machine vision is developed, which can measure parameters of geometric feature of the pipe-end with contactless and high precision. The processing algorithms of image pre-processing and ellipse detection, which are simple, efficient and suitable for the pipe-end surface image, are studied in detail. Focused on the live condition, a new camera calibration method has been used to transform the angle in image into the actual angle.
Based on these studies, the use of Visual C + + programming language developed the research of the geometric feature recognition system of correcting pipe-end based on machine vision, main contents: tube-end image processing, program development of detection and fitting of the ellipse. At last, employing the portble DAQ card and camera CCD and other hardware, the recognition system of geometric feature of correcting pipe-end based on machine vision is established.
The physical simulated experiments have been conducted with the system, which showed that the system operated stably and was high-precision, the punch displacement predicted is reliable. The culmination of the research work is convenient and high-precision measurement of the pipe-end geometry.
本文在板材弯曲智能化控制技术的研究成果基础上,对基于机器视觉的管端矫圆几何特征识别系统的关键问题进行解决。
利用机器视觉和传感器技术,开发了基于机器视觉的管端矫圆几何特征识别系统,实现了管端几何特征参数的非接触、高精度的测量。详细研究了管坯端面图像处理和椭圆检测算法,在试验和结果比较基础上,提出了适合管坯端面的图像处理流程。本文用了适合现场使用的正三角形标定方法。
在上述研究基础上,利用Visual C++编程语言开发了基于机器视觉的管端矫圆几何特征识别系统软件,主要包括:管坯端面图像处理及椭圆检测、拟合的程序开发。最后利用PCI总线数据采集卡、面阵CCD及相关硬件,完成了基于机器视觉的管端矫圆的几何特征识别的硬件系统开发。
利用基于机器视觉的管端矫圆几何特征识别系统进行了物理模拟实验,实验结果表明系统运行稳定,检测精度高。方便和高精度的管端几何形状测量是研究工作的最终成果。
Since the first longitudinal-seam submerged arc welded (LSAW) pipes production line with JCO forming process was established in Julong Steel Pipe Co., Ltd, the unfinished pipe forming process and the correlated technology have been investigated by the researchers. Due to the key technology and the forming press from abroad, the systematical basic research on the forming process has not been conducted yet. And the pipe quality and processing parameters adjustment are conducted according to accumulated experience with the characteristics of large error, high personnel working strength and unstable production quality. As one of the effective method to improve the pipe-end quality, the technology of geometric feature recognition of the pipe-end is introduced to detect the pipe quality.
Based on the research achievements of the intelligent control technology for the sheet metal bending, the key issue of the geometric feature recognition system of correcting pipe-end based on machine vision is resolved in this paper.
Based on machine vision and sensor technology, the geometric feature recognition system of correcting pipe-end based on machine vision is developed, which can measure parameters of geometric feature of the pipe-end with contactless and high precision. The processing algorithms of image pre-processing and ellipse detection, which are simple, efficient and suitable for the pipe-end surface image, are studied in detail. Focused on the live condition, a new camera calibration method has been used to transform the angle in image into the actual angle.
Based on these studies, the use of Visual C + + programming language developed the research of the geometric feature recognition system of correcting pipe-end based on machine vision, main contents: tube-end image processing, program development of detection and fitting of the ellipse. At last, employing the portble DAQ card and camera CCD and other hardware, the recognition system of geometric feature of correcting pipe-end based on machine vision is established.
The physical simulated experiments have been conducted with the system, which showed that the system operated stably and was high-precision, the punch displacement predicted is reliable. The culmination of the research work is convenient and high-precision measurement of the pipe-end geometry.
引文
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10解培成,侯占森,于文光.大直径螺旋埋弧焊管在长输管线上应用前景.鞍山钢铁学院学报, 2002, 25(4): 273-279
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26何大钧,王孝培,罗永建.筒形件拉深CAPP中模糊信息优化技术的应用.锻压技术, 2002(1): 11-14
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34王凤琴,高颖,赵军.基于遗传算法的神经网络优化.燕山大学学报, 2001, 25(3): 235-239
35赵军,郑祖伟,王凤琴.轴对称件拉深成形智能化控制过程中参数实时识别的GA-ENN建模.中国机械工程, 2003, 14(1): 72-74
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38官英平,赵军,苏春建.宽板V形自由弯曲智能化控制过程材料参数识别及最优工艺参数预测.机械工程学报, 2005, 41(4): 199-202
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2李晓红.我国焊管生产现状及发展趋势.钢管, 2008, 37(1): 18-21
3陈宝林.我国建设直缝埋弧焊管机组的前景.钢管, 2000, 29(2): 5-9
4李鹤林.油气输送钢管的发展动向与展望.焊管, 2004, 27(6): 1-11
5张培康.从陕京管道建设看国产埋弧螺旋焊管质量的提高.焊管, 1998, 21(4): 50-51
6尹国耀.库—鄯输油管道达到90年代国际先进水平的依据.焊管, 1999, 22(3): 1-3
7陈三强,胡万志.从库鄯输油管线建设特点探讨西部石油管道发展对策.焊管, 1999, 22(1): 1-3
8冯耀荣,李鹤林.管道钢及管道钢管的研究进展与发展方向(上).石油规划设计, 2005, 16(5): 1-7
9张远生,李延丰.大口径直缝埋弧焊钢管生产线简介.焊管, 2001, 24(6): 35-37
10解培成,侯占森,于文光.大直径螺旋埋弧焊管在长输管线上应用前景.鞍山钢铁学院学报, 2002, 25(4): 273-279
11吴坚.轧钢设备及工艺-钢管生产.东北重型机械学院学报, 1984, 6: 180-197
12陈少杰.螺旋焊管成形工艺研究. [燕山大学博士学位论文]. 1997: 5-8
13张绍庆.螺旋焊接钢管的直径控制.焊管, 1995, 18(6): 34-38
14王关荣.压力容器整圆模的设计和应用.压力容器, 1991, 8(6): 40-44
15李长穆等编译.现代钢管生产.冶金工业出版社, 1982: 271-280
16潘家华.我国管道钢管的发展方向.焊管, 1998, 21(4): 16-20
17杨槐安.西气东输工程简介和管道信息.化工施工技术, 2000, 22(5): 6
18李延丰.螺旋缝埋弧焊管与直缝埋弧焊管之特点.焊管, 1998, 21(3): 1-2
19王晓香.建设大口径直缝埋弧焊管生产线可行性研究的几点说明.焊管, 1998, 21(4): 52-54
20丁大宇.螺旋缝埋弧焊管与直缝埋弧焊管之特点.钢管, 1997, 26(1): 18-20
21张朝生.国外UOE电焊钢管生产技术发展现状.焊管, 1992, 15(3): 54-61
22兰兴昌.我国建设大直径直缝埋弧焊管机组的机组选型.焊管, 1998, 21(4): 41-45
23李宏.直缝埋弧焊钢管生产线预弯工艺.焊管, 2006, 29(1): 55-57
24 W. M. Sing, K. P. Rao. Knowledge-Based Process Layout System for Axisymmetrical Deep Drawing Using Decision Tables. Computer & Industrial Engineering, 1997, 32(2): 299-319
25 G. S. Sekhon R. Singh. An Expert System for Optimal Selection of a Press for a Sheet Metal Operation. Journal of Materials Processing Technology, 1999, 86(1-3): 131-138
26何大钧,王孝培,罗永建.筒形件拉深CAPP中模糊信息优化技术的应用.锻压技术, 2002(1): 11-14
27吕冬,丁柯,何丹农,等.基于神经网络的拉深力智能化预测系统.中国有色金属学报, 2000, 10(3): 420-425
28赵军.圆锥形件拉深成形智能化的研究. [哈尔滨工业大学工学博士学位论文]. 1997: 128-129
29王凤琴.盒形件拉深智能化控制关键技术的研究. [燕山大学工学博士学位论文]. 2003: 92-94
30官英平.板材弯曲智能化控制技术的研究. [燕山大学工学博士学位论文]. 2004: 85-86
31赵军,秦泗吉,曹宏强,等.轴对称曲面件智能化拉深成形过程的解析定量描述.塑性工程学报, 1998, 5(4): 47-48
32赵军,李硕本,吕炎.板材冲压成形的智能化控制技术.塑性工程学报, 1999, 6(4): 10-21
33赵军,罗亚军,官英平,等.基于神经网络的材料性能参数和摩擦系数的实时识别.塑性工程学报, 2001, 8(2): 36-39
34王凤琴,高颖,赵军.基于遗传算法的神经网络优化.燕山大学学报, 2001, 25(3): 235-239
35赵军,郑祖伟,王凤琴.轴对称件拉深成形智能化控制过程中参数实时识别的GA-ENN建模.中国机械工程, 2003, 14(1): 72-74
36王凤琴,赵军,官英平,等.方盒形件拉深破裂预测的研究.塑性工程学报, 2003,10(6): 19-22
37 Zhao Jun, Cao Hong-qiang, Ma Li-xia. Study on intelligent control technology of deep drawing for an axis-symmetric shell part. Journal of Material Processing Technology, 2004, 151: 98-104
38官英平,赵军,苏春建.宽板V形自由弯曲智能化控制过程材料参数识别及最优工艺参数预测.机械工程学报, 2005, 41(4): 199-202
39官英平,赵军,苏春建.宽板V形自由弯曲智能化控制过程解析定量描述.塑性工程学报, 2005, 12(2): 30-33
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