刀具磨损
端铣
机床
钛合金
可靠性(半导体)
机械加工
过程(计算)
刀具
机械工程
铣刀
材料科学
工程类
计算机科学
冶金
合金
功率(物理)
物理
量子力学
操作系统
作者
Xianghui Zhang,Haoyang Yu,Cheng Chao Li,Zhanjiang Yu,Jinkai Xu,Yiquan Li,Huadong Yu
出处
期刊:Micromachines
[MDPI AG]
日期:2022-12-30
卷期号:14 (1): 100-100
被引量:3
摘要
Most in situ tool wear monitoring methods during micro end milling rely on signals captured from the machining process to evaluate tool wear behavior; accurate positioning in the tool wear region and direct measurement of the level of wear are difficult to achieve. In this paper, an in situ monitoring system based on machine vision is designed and established to monitor tool wear behavior in micro end milling of titanium alloy Ti6Al4V. Meanwhile, types of tool wear zones during micro end milling are discussed and analyzed to obtain indicators for evaluating wear behavior. Aiming to measure such indicators, this study proposes image processing algorithms. Furthermore, the accuracy and reliability of these algorithms are verified by processing the template image of tool wear gathered during the experiment. Finally, a micro end milling experiment is performed with the verified micro end milling tool and the main wear type of the tool is understood via in-situ tool wear detection. Analyzing the measurement results of evaluation indicators of wear behavior shows the relationship between the level of wear and varying cutting time; it also gives the main influencing reasons that cause the change in each wear evaluation indicator.
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