网站首页期刊简介编委会过刊目录投稿指南广告合作征订与发行联系我们English
精冲件轮廓缺陷在线检测技术
英文标题:Online detection technology on contour defects for fine blanking parts
作者:张昊武1 彭群2 杨泽亚1 李佳盈1 杜贵江2 李峰2 郭康1 
单位:1.中国机械总院集团北京机电研究所有限公司 2. 中国机械总院集团北京机电研究所有限公司扬州分公司 
关键词:机器视觉 在线检测 精冲件 图像配准 轮廓检测 
分类号:TP391.4; TP23
出版年,卷(期):页码:2022,47(12):206-211
摘要:

 为提高平板厚板型精冲件的轮廓检测速度与精度,基于机器视觉技术,研究了一种轮廓缺陷在线检测技术。利用Canny算子从均值偏移滤波后图像中提取边缘线,然后根据标准轮廓(模板)的尺寸,从中挑选出需要检测的轮廓。由于待检测轮廓与模板存在角度与位移偏差等问题,提出了一种先角度配准、再位置配准的两步图像配准算法,将配准后的待检轮廓与模板进行图形比对,差异图像经过形态学滤波等算法处理,获得缺陷区域的尺寸及位置,由此实现精冲件的在线检测。基于研究成果设计开发了一套零件在线检测系统,并进行了实验验证。结果表明,该系统能够识别的零件精度达0.4 mm,每件的识别时间小于0.3 s,完全能够满足大批量精冲零件的轮廓缺陷在线检测的需求。

  In order to improve the speed and accuracy of contour detection for fine blanking parts of thick and flat plates, an online detection technology for contour defects was studied based on machine vision technology. Then, the edge lines were extracted from the mean shift filtered image by the Canny operator, and according to the size of standard contours (templates), the contours to be detected were selected. Due to the problems of angle and displacement deviation between the contour to be detected and the template, a two-step image registration algorithm was proposed, which first registered the angle and then registered the position, and the registered contour to be detected was graphically compared with the template. Furthermore, the difference image was processed by the algorithms such as morphological filtering to obtain the size and location of the defect area, thereby realizing the online detection of fine blanking parts. Finally, based on the research results, a set of online detection system for parts was designed and developed, and the experimental verification was carried out. The results show that the system can recognize parts with the accuracy of 0.4 mm, and the recognition time of each part is less than 0.3 s, which can fully meet the needs of online detection for contour defects in mass fine blanking parts. 

基金项目:
作者简介:
张昊武(1996-),男,硕士研究生 E-mail:tony_insect@163.com 通信作者:彭群(1971-),男,硕士,研究员 E-mail:pengqun89@163.com
参考文献:

 [1]涂光祺.精冲技术[M].北京:机械工业出版社,2006.


 


Tu G Q.Fine Blanking Technology[M].Beijing:China Machine Press,2006.


 


[2]张俊凯.一种快速的旋转模板匹配算法的设计与实现[D]. 哈尔滨:哈尔滨工业大学,2013.


 


Zhang J K.Design and Implementation of a Novel Template Matching Algorithm Invariant to Rotation[D]. Harbin Harbin Institute of Technology,2013.


 


[3]Zhang R L,Wang L.An image matching evolutionary algorithm based on Hu invariant moments[A].2011 International Conference on Image Analysis and Signal Processing[C].New York:IEEE,2011.


 


[4]Zhou A W,Zheng H,Li M,et al.Defect inspection algorithm of metal surface based on machine vision[A]. 2020 12th International Conference on Measuring Technology and Mechatronics Automation[C]. New York:IEEE,2020.


 


[5]Fernández-Robles L,Azzopardi G,Alegre E,et al. Machine-vision-based identification of broken inserts in edge profile milling heads[J].Robotics and Computer-Integrated Manufacturing, 2017, 44(4): 276-283.


 


[6]黄鹏,郑淇,梁超.图像分割方法综述[J].武汉大学学报:理学版,2020,66(6):519-531.


 


Huang P,Zheng Q,Liang C.Overview of image segmentation methods[J]. Journal of Wuhan University Natural Science Edition, 2020,66(6):519-531.


 


[7]于志斌,胡泓.基于YOLO算法与机器视觉的晶圆片表面缺陷检测研究[J].新型工业化, 2021,11(12):114-117.


 


Yu Z B,Hu H.Research on wafer surface defect detection based on YOLO algorithm and machine vision[J].The Journal of New Industrialization, 2021,11(12):114-117.


 


[8]虞佳佳,张耀,何勇.基于机器视觉的铝镍钴磁性材料外观缺陷检测的研究[J].浙江工业大学学报, 2022,50(2):143-148.


 


Yu J J,Zhang Y,He Y.Research on appearance defect detection of aluminum nickel cobalt magnetic materials based on machine vision[J].Journal of Zhejiang University of Technology,2022,50(2):143-148.


 


[9]柳宗浦.基于机器视觉的小型金属部件表面缺陷检测系统[D].上海: 东华大学,2009.


 


Liu Z P.On Machine Vision based Surface Flaw Detection System for Minitype Metal Parts[D].Shanghai: Donghua University, 2009.


 


[10]He K,Sun J,Tang X.Guided image filtering[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2013,35(6):1397-1409.


 


[11]Yuan L Y,Xue X.Adaptive image edge detection algorithm based on canny operator[A].2015 4th International Conference on Advanced Information Technology and Sensor Application[C].New York: IEEE,2015.


 


[12]仇瑞娜.不规则冲压件轮廓缺陷视觉检测研究[D].天津: 河北工业大学,2018.


 


Qiu R N.Research on Visual Inspection for Contour Defects of Irregular Stamping Parts[D].Tianjin: Hebei University of Technology,2018.

服务与反馈:
文章下载】【加入收藏
《锻压技术》编辑部版权所有

中国机械工业联合会主管  中国机械总院集团北京机电研究所有限公司 中国机械工程学会主办
联系地址:北京市海淀区学清路18号 邮编:100083
电话:+86-010-82415085 传真:+86-010-62920652
E-mail: fst@263.net(稿件) dyjsjournal@163.com(广告)
京ICP备07007000号-9