Lin En-Yu, Chen Ju-Chin, Lien Jenn-Jier James
Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan 701, Taiwan.
Department of Computer Science and Information Engineering, National Kaohsiung University of Science and Technology, Kaohsiung 807, Taiwan.
Sensors (Basel). 2023 Sep 21;23(18):8005. doi: 10.3390/s23188005.
Currently, the majority of industrial metal processing involves the use of taps for cutting. However, existing tap machines require relocation to specialized inspection stations and only assess the condition of the cutting edges for defects. They do not evaluate the quality of the cutting angles and the amount of removed material. Machine vision, a key component of smart manufacturing, is commonly used for visual inspection. Taps are employed for processing various materials. Traditional tap replacement relies on the technician's accumulated empirical experience to determine the service life of the tap. Therefore, we propose the use of visual inspection of the tap's external features to determine whether replacement or regrinding is needed. We examined the bearing surface of the tap and utilized single images to identify the cutting angle, clearance angle, and cone angles. By inspecting the side of the tap, we calculated the wear of each cusp. This inspection process can facilitate the development of a tap life system, allowing for the estimation of the durability and wear of taps and nuts made of different materials. Statistical analysis can be employed to predict the lifespan of taps in production lines. Experimental error is 16 μm. Wear from tapping 60 times is equivalent to 8 s of electric grinding. We have introduced a parameter, thread removal quantity, which has not been proposed by anyone else.
目前，大多数工业金属加工都涉及使用丝锥进行切削。然而，现有的丝锥加工机床需要转移到专门的检测站，并且仅评估切削刃是否存在缺陷。它们不评估切削角度的质量和去除材料的量。机器视觉作为智能制造的关键组成部分，常用于视觉检测。丝锥用于加工各种材料。传统的丝锥更换依赖于技术人员积累的经验来确定丝锥的使用寿命。因此，我们建议通过对丝锥外部特征进行视觉检测，以确定是否需要更换或重磨。我们检查了丝锥的支承面，并利用单幅图像识别切削角、后角和锥角。通过检查丝锥的侧面，我们计算了每个齿尖的磨损情况。该检测过程有助于开发丝锥寿命系统，从而能够估算由不同材料制成的丝锥和螺母的耐用性及磨损情况。可采用统计分析来预测生产线上丝锥的使用寿命。实验误差为16μm。攻丝60次的磨损量相当于8秒的电动磨削量。我们引入了一个其他人尚未提出的参数——螺纹去除量。
