• CN:11-2187/TH
  • ISSN:0577-6686

›› 2011, Vol. 47 ›› Issue (11): 191-198.

• 论文 • 上一篇    

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基于初期磨损统计规律的铣刀快速筛选

张辉;陈五一   

  1. 北京航空航天大学机械工程及自动化学院
  • 发布日期:2011-06-05

Milling Tool Rapid Selection Based on Statistical Law of Initial Wear

ZHANG Hui;CHEN Wuyi   

  1. School of Mechanical Engineering and Automation, Beihang University
  • Published:2011-06-05

摘要: 市场上刀具种类繁多,对于某种应用的刀具筛选来说,选择合适的刀具,极为困难,耗费大量的时间和材料。为了降低筛选难度,需要有新的筛选方法。从295条铣削刀具磨损曲线中提取刀具寿命、磨钝标准、初期磨损值、初期磨损铣削长度等特征参数,计算初期磨损率K0、总磨损率K1以及二者比值K。对K0、K1、K进行了统计分析,得出随机变量K0、K1分别服从对数正态分布,K服从平移的指数分布,K0和K1相互不独立,进而得出铣刀“初期磨损快,刀具寿命短”的统计规律,在此基础上,进一步提出铣刀快速筛选方法。并通过试验验证了该方法的有效性。新方法比传统试验方法极大地节省了试验材料,缩短了试验周期,使得在大范围内优选刀具材料成为可能。

关键词: 初期磨损, 刀具寿命, 统计规律, 铣刀快速筛选

Abstract: At present, there are a variety of cutting tools in the market, so it’s difficult to select a suitable tool for a specific application, thus often spending a great deal of time and materials. To reduce selection difficulty, it’s necessary to develop a new method. Characteristic parameters, namely, tool life, dulling criteria, initial wear value and milling length at initial wear are picked out from 295 milling tool wear curves to calculate initial wear rate K0, final wear rate K1 and the ratio K between the two. Statistic analysis of K0, K1 and K is carried out, the results show that the random variables K0 and K1 comply with lognormal distribution, K complies with translational exponential distribution, K0 and K1 are not independent to each other, thus obtaining the statistical law that the faster the initial wear is, the shorter the tool life will be. Base on this, a milling tool rapid selection method is put forward and validated through tests. This method can greatly save material and time for experiments and make it possible to select best tool material from a large number of candidates.

Key words: Initial wear, Milling tool rapid selection, Statistical law, Tool life

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