面向立铣刀磨损的在机视觉检测方法研究

针对立铣刀在机视觉检测要求,设计了搭建在机床侧窗的伸缩式检测机构,提出用迭代法快速收敛得到刀具磨损区的初阈值,引入类内方差函数改进最大类间方差法,修正传统算法边界模糊、纹理识别不全、对噪声敏感的缺陷。根据灰度矩旋转不变特性,融合Canny算子提取亚像素级磨损边缘,基于图像平面,创建立铣刀磨损轮廓模型,重构切削刃原轮廓,实现立铣刀磨损快速检测。选取5把立铣刀开展铣削实验,将检测系统与影像测量仪的测量值进行对比。结果表明：测量偏差小于0.01 mm,立铣刀生命周期内各磨损阶段的平均准确率均达到93%以上,综合平均准确率达到95.98%,证明了检测系统的准确率与稳定性。

Research on the On-machine Vision Detection Method for End Mill Wear

According to the requirements of on-machine visual inspection of end mills, a telescopic inspection mechanism built on the side window of the machine tool was designed. The iterative method was used to quickly converge to obtain the initial threshold of the tool wear area, and the intra-class variance function was introduced to improve the maximum inter-class variance method,by which the defects of traditional algorithms, such as blurred boundaries, incomplete texture recognition and sensitivity to noise,were fixed.According to the rotation invariant characteristics of the gray moment, the Canny operator was fused to extract the sub-pixel wear edge, and based on the image plane, the wear contour model of the end mill was created, and the original contour of the cutting edge was reconstructed to realize the rapid detection of end mill wear.Finally, 5 end mills were selected to carry out milling experiments, and the measurement values of the detection system and the image measuring instrument were compared.The results show that the measurement deviation is less than 0.01 mm, and the average accuracy rate of each wear stage of the end mill in the life cycle reaches more than 93%, the comprehensive average accuracy rate reaches 95.98%, which proves the accuracy and stability of the detection system.