[1]江 芳,张其亮,邵 倩,等.基于机器视觉的铣刀破损自动化检测研究 [J].计算机技术与发展,2020,30(10):194-198.[doi:10. 3969 / j. issn. 1673-629X. 2020. 10. 034]
　JIANG Fang,ZHANG Qi-liang,SHAO Qian,et al.Study of Automatic Detection of Milling Cutter Damage Based on Machine Vision[J].,2020,30(10):194-198.[doi:10. 3969 / j. issn. 1673-629X. 2020. 10. 034]
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基于机器视觉的铣刀破损自动化检测研究
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
30
期数:
2020年10期
页码:
194-198
栏目:
应用开发研究
出版日期:
2020-10-10

文章信息/Info

Title:
Study of Automatic Detection of Milling Cutter Damage Based on Machine Vision
文章编号:
1673-629X(2020)10-0194-05
作者:
江 芳; 张其亮; 邵 倩; 王雯雯
江苏科技大学 电气与信息工程学院,江苏 张家港 215600
Author(s):
JIANG Fang; ZHANG Qi-liang; SHAO Qian; WANG Wen-wen
School of Electrical and Information Engineering,Jiangsu University of Science and Technology, Zhangjiagang 215600,China
关键词:
机器视觉; 铣刀; 破损检测; 阈值分割; 角点定位
Keywords:
machine vision; milling cutter; defect detection; threshold segmentation; corner detection
分类号:
TP391
DOI:
10. 3969 / j. issn. 1673-629X. 2020. 10. 034
文献标志码:
A
摘要:
随着中国工业智能化的进程不断加快,对刀具工件的质量和生产效率提出了越来越高的要求,及时掌握铣刀的质 量好坏,对于提高生产效率与产品质量具有重要的现实意义。 针对人工检测铣刀破损存在不稳定、效率低、成本高等缺 点,提出了一种基于机器视觉的铣刀破损自动化检测方法。 首先由工业 CCD 相机从不同角度自动采集铣刀的多幅图像, 应用双边滤波、分段线性变换、大津法阈值分割方法对图像进行预处理。 确定铣刀刀具尖端点并在捕获的刀具磨损图像 内优化破损检测区域。 根据铣刀的形状特征提出基于特征角点定位的破损检测方法,检测刀片的实际边界并拟合出理论 边界,实现对铣刀是否存在破损的自动化检测。 实验结果表明,该系统能够实现铣刀破损的快速检测,且检测质量较高, 满足了实际应用需求。
Abstract:
With the development of China’ s industrial intelligentization,higher and higher requirements have been put forward for the quality and production efficiency of tool workpieces. Therefore,it is of great practical significance to know the milling cutter quality in time. Aiming at the disadvantages? ? ? of instability,low efficiency and high cost in manual detection of milling cutter damage,we propose an automatic detection method of milling cutter damage based on machine vision. Firstly,multiple images of milling cutter are acquired automatically by industrial CCD camera from different angles,and the images are preprocessed by bilateral filtering,piecewise linear transformation and Otsu threshold segmentation. Then determine? ?the tip of the milling cutter and optimize the fracture detection area within the captured tool wear image. According to the shape features of milling cutter,a defect detection method based on feature corner points is proposed to detect the actual boundary of the blade and fit the theoretical boundary, so as to realize the automatic detection of whether the milling cutter is damaged or not. The experiment shows that the system can realize the rapid detection of the milling cutter damage with high detection quality,which meets the practical application requirements.

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更新日期/Last Update: 2020-10-10