超声TOFD焊缝缺陷图像识别系统研究
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摘要
超声TOFD(time of flight diffraction)检测系统是通过检测入射超声纵波在缺陷端部产生的衍射波信号,并根据其传播时间差进行缺陷定量与定位的方法。TOFD技术具有缺陷检测结果直观、准确的特点。超声TOFD检测技术具有原理简单、操作便利、检测速度快、对焊缝中裂纹类缺陷检出率高、特别适合于大厚件焊缝检测等优点得到了广泛的应用。
本文设计了TOFD检测系统的手动扫查装置,编写了基于VC++的图像处理系统。为了准确定位缺陷深度,针对由于工件表面不平整、扫查速度突变等原因造成检测图像发生畸变弯曲现象,根据TOFD成像原理,采用了基于峰值搜索算法的直通波拉直技术,该方法能够很好地矫正图像,使直通波保持在相同的水平位置；实际焊缝检测过程中采集数据量较大,可以在直通波拉直的基础上提取有效焊缝区域,减少了后期图像处理的数据量,提高了后续处理的效率。
缺陷判读作为超声TOFD检测的重要部分主要是由人工操作来完成,消耗了检测人员大量的时间和精力。另外受检测人员的知识、经验和熟练程度的影响,缺陷判读及检测结果往往存在误差,特别是在大量数据处理过程中,甚至会发生错误。因此,为了提高工作效率、降低误判率,本文提出通过频域变换处理后建立D扫图像的背景模型,利用背景减除算法提取有效的焊缝缺陷图形,实现焊缝缺陷目标的自动提取,提高了焊缝缺陷的检测效率及准确性。
本文设计的超声TOFD检测系统包括十字光标、抛物线指针光标等人工检测模块,同时可分步实现图像拉直、焊缝区域提取、焊缝缺陷图形提取等功能,验证自动提取焊缝缺陷图形的正确性,具有检测图像清晰,操作过程简单,缺陷位置计算准确等特点。
Time of Flight Diffraction Ultrasonic detection method is based on the measurements of the travel time of the echoes diffracted by the defect. It has three kinds of display modes called A-scan, B-scan and D-scan, the detection result is direct and precise. TOFD Ultrasonic detection method has simple principle, convenient operations, fast detection speed, high crack defects detection rate, especially suitable for the thick weld testing and with many other advantages it is widely used in many fields.
This paper designed a manual scanning device for the TOFD detection system, write the image processing system based on VC++6.0. In order to locate the depth of defect accurately, due to the image distortion caused by the roughness of surface, or the scanning velocity mutation, and according to the principle of TOFD detection, straighten the lateral waves based on the peak search algorithm, corrected the image very well and make the lateral waves remain at the same level; The actual weld inspection process collects a large amount of data, so extraction the effective weld area based on the previous process, reduced the data of the image, and improve the efficiency of the processing.
As an important part of TOFD detection, defect interpretation is mainly accomplished by people, waste a lot of time and energy. In addition, due to the personnel knowledge, experiences and the proficiency of the detector, especially when there is a large amount of data, it may get the wrong result. Therefore, in order to improve work efficiency, and reduce the error rate, In this paper, rebuild the image background of D-scan based on the frequency domain filtering, and using the background difference method to extract effective weld defects, extract the welding defects automatically, improves the efficiency and accuracy of the weld detection.
The TOFD inspection system in this paper includes inspection modules such as cross curse and parabola pointer curse, it can straight the lateral wave and extract the effective weld region, according to the original image use the frequency filtering process rebuild the background image, and get the right defects automatically. The experiment shows that this method can extract defect targets accurately.
本文设计了TOFD检测系统的手动扫查装置,编写了基于VC++的图像处理系统。为了准确定位缺陷深度,针对由于工件表面不平整、扫查速度突变等原因造成检测图像发生畸变弯曲现象,根据TOFD成像原理,采用了基于峰值搜索算法的直通波拉直技术,该方法能够很好地矫正图像,使直通波保持在相同的水平位置；实际焊缝检测过程中采集数据量较大,可以在直通波拉直的基础上提取有效焊缝区域,减少了后期图像处理的数据量,提高了后续处理的效率。
缺陷判读作为超声TOFD检测的重要部分主要是由人工操作来完成,消耗了检测人员大量的时间和精力。另外受检测人员的知识、经验和熟练程度的影响,缺陷判读及检测结果往往存在误差,特别是在大量数据处理过程中,甚至会发生错误。因此,为了提高工作效率、降低误判率,本文提出通过频域变换处理后建立D扫图像的背景模型,利用背景减除算法提取有效的焊缝缺陷图形,实现焊缝缺陷目标的自动提取,提高了焊缝缺陷的检测效率及准确性。
本文设计的超声TOFD检测系统包括十字光标、抛物线指针光标等人工检测模块,同时可分步实现图像拉直、焊缝区域提取、焊缝缺陷图形提取等功能,验证自动提取焊缝缺陷图形的正确性,具有检测图像清晰,操作过程简单,缺陷位置计算准确等特点。
Time of Flight Diffraction Ultrasonic detection method is based on the measurements of the travel time of the echoes diffracted by the defect. It has three kinds of display modes called A-scan, B-scan and D-scan, the detection result is direct and precise. TOFD Ultrasonic detection method has simple principle, convenient operations, fast detection speed, high crack defects detection rate, especially suitable for the thick weld testing and with many other advantages it is widely used in many fields.
This paper designed a manual scanning device for the TOFD detection system, write the image processing system based on VC++6.0. In order to locate the depth of defect accurately, due to the image distortion caused by the roughness of surface, or the scanning velocity mutation, and according to the principle of TOFD detection, straighten the lateral waves based on the peak search algorithm, corrected the image very well and make the lateral waves remain at the same level; The actual weld inspection process collects a large amount of data, so extraction the effective weld area based on the previous process, reduced the data of the image, and improve the efficiency of the processing.
As an important part of TOFD detection, defect interpretation is mainly accomplished by people, waste a lot of time and energy. In addition, due to the personnel knowledge, experiences and the proficiency of the detector, especially when there is a large amount of data, it may get the wrong result. Therefore, in order to improve work efficiency, and reduce the error rate, In this paper, rebuild the image background of D-scan based on the frequency domain filtering, and using the background difference method to extract effective weld defects, extract the welding defects automatically, improves the efficiency and accuracy of the weld detection.
The TOFD inspection system in this paper includes inspection modules such as cross curse and parabola pointer curse, it can straight the lateral wave and extract the effective weld region, according to the original image use the frequency filtering process rebuild the background image, and get the right defects automatically. The experiment shows that this method can extract defect targets accurately.
引文
[1]沈功田,张万岭.特种设备无损检测技术综述.无损检测.2006,28(1)：34-39
[2]张锐,万明习.超声衍射回波渡越时间方法焊接裂纹原位定量无损估计.机械工程学报.2000,36(5)：54-57
[3]吴朝晖.超声无损检测的应用与探讨.宁波工程学院学报.2005,17(4)：1-3
[4]中国机械工程学会无损检测学会编,无损检测概论,北京：机械工业出版社,1993.16-32
[5]Print P. Carter, TIME-OF-FLIGHT DIFFRACTION COURSE(Level I and II),Lavender International NDT Consultancy Services Ltd,1999
[6]H. Hatanaka, N. Ido, M. Furikoma, et al. Application of ultrasonic TOFD method for welds of LNG storage tanks. Ishikawajima-Harima Giho/IHI Engineering Review. 2002, 42(3):151~156
[7]A. Kechida, R. Drai and M. Khelil.2D Gabor functions and FCMI algorithm for flaws detection in ultrasonic images. Transactions on Engineering, Computing and Technology. 2005, (9):1305~5313
[8]K. Maalmi, A. E. Ouaazizi, R. Benslimane, et al. Crack defect detection and localization usinggenetic-based inverse voting Hough transform.Proceedings-International Conference on Pattern Recognition,2002,16(3):257~260
[9]中国无损检测学会编译,超声波探伤,北京：机械工业出版社,1987
[10]李衍.超声TOFD法原理和标准,无损检测,2003,27(3)
[11]李衍.焊缝超声TOFD法探伤和定量新技术,无损探伤,2003,27(5)
[12]李衍.焊缝超声TOFD法探伤和定量新技术(续),无损探伤,2003,27(6)
[13]刚铁,迟大钊,袁媛.基于合成孔径聚焦的超声TOFD检测技术及图像增强.焊接学报.2006,27(10)
[14]迟大钊.基于超声TOFD法的焊缝缺陷表征研究.哈尔滨工业大学博士论文.2007
[15]黄江中.焊接缺陷的超声衍射信号分析与图像处理.哈尔滨工业大学硕士论文.2009
[16]盛朝阳.超声TOFD检测信号采集及缺陷识别方法研究.哈尔滨工业大学硕士论 文.2007
[17]张锐,万明习.超声衍射—回波渡越时间方法焊接裂纹原位定量无损估计.机械工程学报.2000,36(5)：54-57
[18]徐书根,王威强,宋明大,等.2.25Cr1Mo钢试块缺陷的超声TOFD检测.无损检测.2007,29(11)：627-629
[19]T. L. Chen, P. W. Que, Q. Zhang, et al. Ultrasonic nondestructive testingaccurate sizing and locating technique based on time-of-flight-diffraction method. Russian Journal of Nondestructive Testing. 2005,41(10):594-601
[20]张平.超声衍射时差检测技术在中国的应用进展[J].无损检测,2008,30(7)
[21]Chariesworth JP, TelnPle JAG. Engineering applieation of ultrasonic time-of-flight-diffraetion[M].Seeond edition. London: Research Studies Press Ltd,2001
[22]薛永盛,袁军生TOFD检测中典型缺陷定性图谱分析.云南水力发电.2008,24(4)：76-78
[23]王树文,闫成新,张天序.数学形态学在图像处理中的应用.计算机工程与应用,2004(32)：p.89-92
[24]Thiran, J. B. Macq. Morphological feature extraction for the classification of digital images of cancerous tissues. Biomedical Engineering, IEEE Transactions on, 2002. 43(10):p.1011-1020
[25]赵亮强.基于超声衍射时差法的焊接缺陷自动识别方法研究.上海交通大学硕士论文.2011.1
[26]徐振.超声TOFD缺陷检测成像处理系统的研制.上海交通大学硕士论文
[27]李衍.超声TOFD检测读谱.无损探伤.2010,34(5)
[28]李衍.超声TOFD原理和方法要领.2007,29(2)
[29]李衍.超声TOFD原理和方法精要.无损探伤.2006,31(6)
[30]李衍ASME法规对超声TOFD法的新规定.无损检测.2007,29(5)
[31]李衍.超声TOFD法的基础试验.无损探伤.2003,27(2)
[32]李衍.欧盟TOFD技术新标准.无损探伤.2008,32(3)
[33]孔令昌.TOFD检测技术及其工艺参数设置.无损检测.2010,32(7)
[34]张平.超声衍射时差检测技术在中国的应用进展.无损检测.2008,30(7)
[35]曹玉雯.超声TOFD的缺陷检测与定量研究.北京化工大学硕士论文
[36]刘富君,丁守宝,胡东明.国内TOFD检测技术的应用进展.无损检测.2009,31(10)
[37]马云,王贺,张晓光.基于形态学的焊接图像缺陷检测方法研究.计算机测量与控制.2010.18(5)
[38]杨晖,曲秀杰.图像分割方法综述.电脑开发与应用.2004,18(3)
[39]孙吉花.背景减除的算法研究.国防科学技术大学硕士论文
[40]British TOFD Standard BS 7706. Guide to Calibration and Setting-up of the Ultrasonic Time of Flight Diffraction (TOFD) Technique for Defect Detection, Location and Sizing of Flaws.1993:1-37
[41]吕品.基于超声TOFD法的厚板铝合金焊缝缺陷识别.哈尔滨工业大学硕士论文.2005
[42]龚铭.无损检测中涡流焊缝识别处理机的实现与TOFD缺陷定位算法的研究.上海交通大学硕士论文.2007
[43]P. Moura, R. Silva and H.S. Siqueira. Pattern Recognition of Weld Defects in Preprocessed TOFD Signals Using Linear Classifiers. Journal of NondestructiveEvaluation.2004,23(4):163-172
[44]迟大钊,刚铁,袁媛.面状缺陷超声TOFD法信号和图像的特征与识别.焊接学报.2005,26(11)
[45]龚铭,朱杰.边缘检测在TOFD扫描图像中的应用.电子测量技术.2007,30(7)
[46]刚铁,徐艳,迟大钊.铝合金焊缝超声TO FD检测的信号特征.焊接学报.2005,26(8)
[47]梁宏林,滕永平,吕香慧.用超声衍射时差法对焊缝缺陷定性表征.无损检测.2006,28(1)
[48]韩寒,冯乃章.超声图像去噪方法.计算机工程与应用.2011,47(26)：193-195
[49]刘培锋,刘红秀.超声图像预处理方法的改进研究.检验医学与临床.2010,7(8)
[50]Gonzalez, R.C., R.E. Woods,阮秋琦,等.数字图像处理.北京：电子工业出版社.2007
[2]张锐,万明习.超声衍射回波渡越时间方法焊接裂纹原位定量无损估计.机械工程学报.2000,36(5)：54-57
[3]吴朝晖.超声无损检测的应用与探讨.宁波工程学院学报.2005,17(4)：1-3
[4]中国机械工程学会无损检测学会编,无损检测概论,北京：机械工业出版社,1993.16-32
[5]Print P. Carter, TIME-OF-FLIGHT DIFFRACTION COURSE(Level I and II),Lavender International NDT Consultancy Services Ltd,1999
[6]H. Hatanaka, N. Ido, M. Furikoma, et al. Application of ultrasonic TOFD method for welds of LNG storage tanks. Ishikawajima-Harima Giho/IHI Engineering Review. 2002, 42(3):151~156
[7]A. Kechida, R. Drai and M. Khelil.2D Gabor functions and FCMI algorithm for flaws detection in ultrasonic images. Transactions on Engineering, Computing and Technology. 2005, (9):1305~5313
[8]K. Maalmi, A. E. Ouaazizi, R. Benslimane, et al. Crack defect detection and localization usinggenetic-based inverse voting Hough transform.Proceedings-International Conference on Pattern Recognition,2002,16(3):257~260
[9]中国无损检测学会编译,超声波探伤,北京：机械工业出版社,1987
[10]李衍.超声TOFD法原理和标准,无损检测,2003,27(3)
[11]李衍.焊缝超声TOFD法探伤和定量新技术,无损探伤,2003,27(5)
[12]李衍.焊缝超声TOFD法探伤和定量新技术(续),无损探伤,2003,27(6)
[13]刚铁,迟大钊,袁媛.基于合成孔径聚焦的超声TOFD检测技术及图像增强.焊接学报.2006,27(10)
[14]迟大钊.基于超声TOFD法的焊缝缺陷表征研究.哈尔滨工业大学博士论文.2007
[15]黄江中.焊接缺陷的超声衍射信号分析与图像处理.哈尔滨工业大学硕士论文.2009
[16]盛朝阳.超声TOFD检测信号采集及缺陷识别方法研究.哈尔滨工业大学硕士论 文.2007
[17]张锐,万明习.超声衍射—回波渡越时间方法焊接裂纹原位定量无损估计.机械工程学报.2000,36(5)：54-57
[18]徐书根,王威强,宋明大,等.2.25Cr1Mo钢试块缺陷的超声TOFD检测.无损检测.2007,29(11)：627-629
[19]T. L. Chen, P. W. Que, Q. Zhang, et al. Ultrasonic nondestructive testingaccurate sizing and locating technique based on time-of-flight-diffraction method. Russian Journal of Nondestructive Testing. 2005,41(10):594-601
[20]张平.超声衍射时差检测技术在中国的应用进展[J].无损检测,2008,30(7)
[21]Chariesworth JP, TelnPle JAG. Engineering applieation of ultrasonic time-of-flight-diffraetion[M].Seeond edition. London: Research Studies Press Ltd,2001
[22]薛永盛,袁军生TOFD检测中典型缺陷定性图谱分析.云南水力发电.2008,24(4)：76-78
[23]王树文,闫成新,张天序.数学形态学在图像处理中的应用.计算机工程与应用,2004(32)：p.89-92
[24]Thiran, J. B. Macq. Morphological feature extraction for the classification of digital images of cancerous tissues. Biomedical Engineering, IEEE Transactions on, 2002. 43(10):p.1011-1020
[25]赵亮强.基于超声衍射时差法的焊接缺陷自动识别方法研究.上海交通大学硕士论文.2011.1
[26]徐振.超声TOFD缺陷检测成像处理系统的研制.上海交通大学硕士论文
[27]李衍.超声TOFD检测读谱.无损探伤.2010,34(5)
[28]李衍.超声TOFD原理和方法要领.2007,29(2)
[29]李衍.超声TOFD原理和方法精要.无损探伤.2006,31(6)
[30]李衍ASME法规对超声TOFD法的新规定.无损检测.2007,29(5)
[31]李衍.超声TOFD法的基础试验.无损探伤.2003,27(2)
[32]李衍.欧盟TOFD技术新标准.无损探伤.2008,32(3)
[33]孔令昌.TOFD检测技术及其工艺参数设置.无损检测.2010,32(7)
[34]张平.超声衍射时差检测技术在中国的应用进展.无损检测.2008,30(7)
[35]曹玉雯.超声TOFD的缺陷检测与定量研究.北京化工大学硕士论文
[36]刘富君,丁守宝,胡东明.国内TOFD检测技术的应用进展.无损检测.2009,31(10)
[37]马云,王贺,张晓光.基于形态学的焊接图像缺陷检测方法研究.计算机测量与控制.2010.18(5)
[38]杨晖,曲秀杰.图像分割方法综述.电脑开发与应用.2004,18(3)
[39]孙吉花.背景减除的算法研究.国防科学技术大学硕士论文
[40]British TOFD Standard BS 7706. Guide to Calibration and Setting-up of the Ultrasonic Time of Flight Diffraction (TOFD) Technique for Defect Detection, Location and Sizing of Flaws.1993:1-37
[41]吕品.基于超声TOFD法的厚板铝合金焊缝缺陷识别.哈尔滨工业大学硕士论文.2005
[42]龚铭.无损检测中涡流焊缝识别处理机的实现与TOFD缺陷定位算法的研究.上海交通大学硕士论文.2007
[43]P. Moura, R. Silva and H.S. Siqueira. Pattern Recognition of Weld Defects in Preprocessed TOFD Signals Using Linear Classifiers. Journal of NondestructiveEvaluation.2004,23(4):163-172
[44]迟大钊,刚铁,袁媛.面状缺陷超声TOFD法信号和图像的特征与识别.焊接学报.2005,26(11)
[45]龚铭,朱杰.边缘检测在TOFD扫描图像中的应用.电子测量技术.2007,30(7)
[46]刚铁,徐艳,迟大钊.铝合金焊缝超声TO FD检测的信号特征.焊接学报.2005,26(8)
[47]梁宏林,滕永平,吕香慧.用超声衍射时差法对焊缝缺陷定性表征.无损检测.2006,28(1)
[48]韩寒,冯乃章.超声图像去噪方法.计算机工程与应用.2011,47(26)：193-195
[49]刘培锋,刘红秀.超声图像预处理方法的改进研究.检验医学与临床.2010,7(8)
[50]Gonzalez, R.C., R.E. Woods,阮秋琦,等.数字图像处理.北京：电子工业出版社.2007
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