航空学报 > 2022, Vol. 43 Issue (7): 425593-425593   doi: 10.7527/S1000-6893.2021.25593

基于机器视觉的立铣刀几何与状态参数在机检测

刘占, 张俊, 尹佳, 赵万华   

  1. 西安交通大学 机械制造系统工程国家重点实验室, 西安 710054
  • 收稿日期:2021-03-29 修回日期:2021-07-12 发布日期:2021-07-09
  • 通讯作者: 张俊,E-mail:junzhang@xjtu.edu.cn E-mail:junzhang@xjtu.edu.cn
  • 基金资助:
    国家重点研发计划(2018YFB1701901);国家自然科学基金(51675417)

On-machine detection of geometric and state parameters of end mills based on machine vision

LIU Zhan, ZHANG Jun, YIN Jia, ZHAO Wanhua   

  1. State Key Laboratory for Manufacturing Systems Engineering, Xi'an Jiaotong University, Xi'an 710054, China
  • Received:2021-03-29 Revised:2021-07-12 Published:2021-07-09
  • Supported by:
    National Key R&D Program of China (2018YFB1701901);National Natural Science Foundation of China (51675417)

摘要: 为解决航空结构件加工过程中频繁换刀导致的刀具及其参数装错问题,应用机器视觉测量系统实现了铣刀几何与状态参数的在机检测。以整体式立铣刀为研究对象,对主轴旋转状态下刀具动态图像轮廓进行提取,分别研究了刀尖圆角、直径以及悬长等参数的视觉测量算法。针对悬长测量过程中因相机视野过大导致的成像偏差问题,提出偏差修正算法,提高了刀具悬长的测量精度。最后,在数控机床上对本文提出的刀具几何与状态参数在机检测方法进行可行性验证。研究表明:该方法所检测刀具参数最大相对测量误差为0.51%,精度高且测量系统性能稳定,能够有效实现航空结构件加工过程中刀具几何与状态参数的在机检测。

关键词: 机器视觉, 几何与状态参数, 立铣刀, 数控加工, 图像处理

Abstract: To prevent the tool installation errors caused by frequent changes of tools during the aeronautical components machining, a detection system based on machine vision is proposed to measure geometric and state parameters of milling cutter. The end mill is taken as the research object, and its dynamic image contour under the state of spindle rotation is extracted. Besides, the measurement algorithm for cutting edge radius, tool diameter and overhang length are also developed. To demonstrate the visual deviation caused by the camera's large view during the measurement of overhang length, the deviation correction algorithm is further studied to improve the measurement accuracy. Finally, the proposed method is verified on the CNC machine tool. The results show that the maximum error is 0.51% and the device achieves good repeatability and high precision, which can realize the on-machine detection of tool geometric and state parameters.

Key words: machine vision, geometric and state parameters, end mill, CNC machining, image processinghttp

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