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  • 标题:Research on tool wear prediction based on Archard agglomeration scavenging theory
  • 作者:Weichao Zhang ; Fan Zou ; Yuan Li
  • 期刊名称:Advances in Mechanical Engineering
  • 印刷版ISSN:1687-8140
  • 电子版ISSN:1687-8140
  • 出版年度:2017
  • 卷号:9
  • 期号:10
  • DOI:10.1177/1687814017724086
  • 语种:English
  • 出版社:Sage Publications Ltd.
  • 摘要:Nickel-based superalloy Inconel 718 has been widely used in the modern aviation field, however, its cutting performance is poor. This performance not only affects the effectiveness of the use of the tool but also reduces the efficiency of production. In this article, the cemented carbide tools cutting nickel-based superalloy Inconel 718 was taken as an example to analyze the tool wear mechanism. The wear prediction model of tool wear with cutting parameters and cutting time was established according to the Archard agglomeration scavenging theory. Using the orthogonal test, the multiple regression analysis method was used to obtain the parameters of the model with the help of EXCELL. Then, the prediction model was verified from two directions. Finally a real-time monitoring method of tool wear based on cutting parameters was proposed.
  • 关键词:Tool wear; Inconel 718; prediction mode; Archard agglomeration scavenging theory; orthogonal test
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