基于图像处理的磨削件表面粗糙度在线检测研究
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摘要
针对表面粗糙度检测的离线性,提出了一种基于图像处理的表面粗糙度在线检测方法。由于工件和摄像装置之间的相对运动,图像产生模糊。论文以运动模糊图像的退化模型为基础,采用迭代盲解卷积算法和正则化处理分离迭代过程中的噪声残差,得到点扩展函数的估计值;并采用点锐度函数进行清晰度评价;选用灰度差分统计法对图像进行分析。实验结果得出了对比度、角度方向二阶矩和熵与表面粗糙度的关系,验证了基于图像处理的表面粗糙度在线检测方法的可行性。
Aiming at the off-line and non-real-time performance of the surface roughness of grinding parts,an on-line detection method of surface roughness of grinding parts based on machine vision technology is proposed. Due to the relative movement between the workpiece and the imaging device,the image is blurred. Based on the degenerate model of motion blurred image,the noise residuals in the iterative process of the iterative blind deconvolution algorithm are obtained by using the iterative blind deconvolution algorithm and the regularization process. The parameter estimation of the extended function of the motion blurred image points is given. And the sharp image is obtained by using the point sharpness function. The gray scale difference statistic method based on Gabor wavelet transform is used to analyze the texture of the clear image. The experimental results show the relationship between the three texture parameters and the surface roughness of the second moment and the entropy of the contrast,and the feasibility of the on-line detection method of the surface roughness of the grinding tool based on the machine vision technology is verified.
Aiming at the off-line and non-real-time performance of the surface roughness of grinding parts,an on-line detection method of surface roughness of grinding parts based on machine vision technology is proposed. Due to the relative movement between the workpiece and the imaging device,the image is blurred. Based on the degenerate model of motion blurred image,the noise residuals in the iterative process of the iterative blind deconvolution algorithm are obtained by using the iterative blind deconvolution algorithm and the regularization process. The parameter estimation of the extended function of the motion blurred image points is given. And the sharp image is obtained by using the point sharpness function. The gray scale difference statistic method based on Gabor wavelet transform is used to analyze the texture of the clear image. The experimental results show the relationship between the three texture parameters and the surface roughness of the second moment and the entropy of the contrast,and the feasibility of the on-line detection method of the surface roughness of the grinding tool based on the machine vision technology is verified.
引文
[1]XueL FNaghdy,C.D. Cook[C]//In process surface roughness estimation grinding,2003;2-4.
[2]石建.基于声发射技术磨削表面粗糙度在线检测研究[D].长春:长春理工大学,2014:11-13.SHI Jian. On-line detection of surface roughness based on acoustic emission technology[D]. Changchun:Changchun University of Science and Technology,2014:11-13.
[3]B. Y.Lee,H. JUAN,S. F.YU. A study of Comput er Vision for Measuring Surface Roughness in the Turning Process[J]. Advanced Manufacturing Technology,2002:19(4):295-301.
[4]Giuseppe Schirripa Spagnolo,Lorenzo Cozzella,Fabio Leccese. Viability of an optoelectronic system for real time roughness measurement[J]. Measurement,2014;58:537-543.
[5]O.V.Angelsky. Optical Correlation Techniques and Applications[J]. SPIE,Bellingham,USA,2007:3-5.
[6]梁嵘,李达成,曹芒,等.在线测量表面粗糙度的共光路激光外差干涉仪[J].光学学报,1999,19(7):958-961.LIANG Wei,LI Dian,CAO Mang,et al. A common optical path laser heterodyne interferometer for measuring surface roughness on-line[J]. Acta Optica Sinica,1999,19(7):958-961.
[7]易怀安,刘坚,路恩会.基于图像清晰度评价的磨削表面粗糙度检测方法[J].机械工程学报,2016,52(16).YI Huaian,LIU Jian,LU Enhui. Method for detecting surface roughness of grinding based on image sharpness evaluation[J]. Journal of Mechanical Engineering,2016,52(16).
[8] Al-Kindi GA,Shirinzadeh B. An evaluation of surface roughness parameters measurements using vision-data. International Journal of Machine Tools and Manufacture,2007,47:697-708.
[9]NAMMI S,RAMAMOORTHY B. Effect of surface lay in the surface roughness evaluation using machine vision[J].Optik,2014;125:3954-3960.
[10]JOSHIN,SZELISKl R,KRIEGMAN D. PSF estimation using sharp edge prediction[C]//IEEE Conference on Computer Vision and PaRern Recognition,2008:1-8.
[11]Rafael C.Gonzalez Richard E.Woods Steven L.Eddins数字图像处理的Matlab实现(第2版)[M].北京:清华大学出版社,2015,9:123-128.Rafael C. Gonzalez Richard E. Woods Steven L. Eddins Matlab implementation of digital image processing(2nd edition)[M]. Beijing:Tsinghua University Press,2015,9:123-128.
[12]AYERSGR,DAINTY J C. Iterative blind deconvolution method and its applications[J]. Opt. Lett,1988,13(7):547-549.
[13]Xu Guili,Liu Xiaoxia,Tian Yupeng,et al. Image Charity evaluation-function M ethod[J]. Inf rared and Laser En gineering,2009,38(1):180-184.
[14]Zhang Xia,Zhang Bing,ZhaoYong chao,et al. Image Quality Assessment for the Infrared Multi-Spectral Scanner of the Chines e-Brazil Earth Resources Satellite[J].Journal of Image and Graphics,2002,7A(6):581-586.
[15]Rafael C.Gonzalez等.数字图像处理的Matlab实现[M].北京:清华大学出版社,2013,4:106-108.Rafael C. Gonzalez et al. MATLAB implementation of digital image processing[M]. Beijing:Tsinghua University Press,2013,4:106-108.
[16]朱希安等.小波分析及其在数字图像处理中的应用[M].北京:电子工业出版社,2012:218-220.ZHU Xi'an,et al. Wavelet analysis and its application in digital image processing[M]. Beijing:Electronic Industry Press,2012:218-220.
[17]Milan Sonka,Vaclav Hlavac,Roger Boyle.Imange Processing,Analysis,and Machine Vision[M].北京:清华大学出版社,1993:516-525.Milan Sonka,Vaclav Hlavac,Roger Boyle. Imange Processing,Analysis,and Machine Vision[M]. Beijing:Tsinghua University Press,1993:516-525.
[18]李柏年等. Matlab数据分析方法[M].北京:机械工业出版社,2012:105-120.LI Bainian,et al. MATLAB data analysis method[M].Beijing:Mechanical Industry Press,2012:105-120.
[2]石建.基于声发射技术磨削表面粗糙度在线检测研究[D].长春:长春理工大学,2014:11-13.SHI Jian. On-line detection of surface roughness based on acoustic emission technology[D]. Changchun:Changchun University of Science and Technology,2014:11-13.
[3]B. Y.Lee,H. JUAN,S. F.YU. A study of Comput er Vision for Measuring Surface Roughness in the Turning Process[J]. Advanced Manufacturing Technology,2002:19(4):295-301.
[4]Giuseppe Schirripa Spagnolo,Lorenzo Cozzella,Fabio Leccese. Viability of an optoelectronic system for real time roughness measurement[J]. Measurement,2014;58:537-543.
[5]O.V.Angelsky. Optical Correlation Techniques and Applications[J]. SPIE,Bellingham,USA,2007:3-5.
[6]梁嵘,李达成,曹芒,等.在线测量表面粗糙度的共光路激光外差干涉仪[J].光学学报,1999,19(7):958-961.LIANG Wei,LI Dian,CAO Mang,et al. A common optical path laser heterodyne interferometer for measuring surface roughness on-line[J]. Acta Optica Sinica,1999,19(7):958-961.
[7]易怀安,刘坚,路恩会.基于图像清晰度评价的磨削表面粗糙度检测方法[J].机械工程学报,2016,52(16).YI Huaian,LIU Jian,LU Enhui. Method for detecting surface roughness of grinding based on image sharpness evaluation[J]. Journal of Mechanical Engineering,2016,52(16).
[8] Al-Kindi GA,Shirinzadeh B. An evaluation of surface roughness parameters measurements using vision-data. International Journal of Machine Tools and Manufacture,2007,47:697-708.
[9]NAMMI S,RAMAMOORTHY B. Effect of surface lay in the surface roughness evaluation using machine vision[J].Optik,2014;125:3954-3960.
[10]JOSHIN,SZELISKl R,KRIEGMAN D. PSF estimation using sharp edge prediction[C]//IEEE Conference on Computer Vision and PaRern Recognition,2008:1-8.
[11]Rafael C.Gonzalez Richard E.Woods Steven L.Eddins数字图像处理的Matlab实现(第2版)[M].北京:清华大学出版社,2015,9:123-128.Rafael C. Gonzalez Richard E. Woods Steven L. Eddins Matlab implementation of digital image processing(2nd edition)[M]. Beijing:Tsinghua University Press,2015,9:123-128.
[12]AYERSGR,DAINTY J C. Iterative blind deconvolution method and its applications[J]. Opt. Lett,1988,13(7):547-549.
[13]Xu Guili,Liu Xiaoxia,Tian Yupeng,et al. Image Charity evaluation-function M ethod[J]. Inf rared and Laser En gineering,2009,38(1):180-184.
[14]Zhang Xia,Zhang Bing,ZhaoYong chao,et al. Image Quality Assessment for the Infrared Multi-Spectral Scanner of the Chines e-Brazil Earth Resources Satellite[J].Journal of Image and Graphics,2002,7A(6):581-586.
[15]Rafael C.Gonzalez等.数字图像处理的Matlab实现[M].北京:清华大学出版社,2013,4:106-108.Rafael C. Gonzalez et al. MATLAB implementation of digital image processing[M]. Beijing:Tsinghua University Press,2013,4:106-108.
[16]朱希安等.小波分析及其在数字图像处理中的应用[M].北京:电子工业出版社,2012:218-220.ZHU Xi'an,et al. Wavelet analysis and its application in digital image processing[M]. Beijing:Electronic Industry Press,2012:218-220.
[17]Milan Sonka,Vaclav Hlavac,Roger Boyle.Imange Processing,Analysis,and Machine Vision[M].北京:清华大学出版社,1993:516-525.Milan Sonka,Vaclav Hlavac,Roger Boyle. Imange Processing,Analysis,and Machine Vision[M]. Beijing:Tsinghua University Press,1993:516-525.
[18]李柏年等. Matlab数据分析方法[M].北京:机械工业出版社,2012:105-120.LI Bainian,et al. MATLAB data analysis method[M].Beijing:Mechanical Industry Press,2012:105-120.
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