Tool wear monitoring for optimizing cutting conditions

被引：17

作者：

Obikawa, T ^{[1
]}

Kaseda, C ^{[1
]}

Matsumura, T ^{[1
]}

Gong, WG ^{[1
]}

Shirakashi, T ^{[1
]}

机构：

[1] TOKYO DENKI UNIV, DEPT ENGN MECH, CHIYODA KU, TOKYO 101, JAPAN

来源：

JOURNAL OF MATERIALS PROCESSING TECHNOLOGY | 1996年 / 62卷 / 04期

关键词：

cutting; tool wear; monitoring; optimization;

D O I：

10.1016/S0924-0136(96)02438-7

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

Tool flank wear during turning is monitored through artificial neural networks of which the input consists of the AR coefficients representing the power spectrum of cutting force and some other parameters. The order of AR model is effectively determined by AIC. The monitored and measured flank wear agree very well. The flank wear rate monitored is further used to adaptively revise the characteristic constants of a wear equation, by which the wear rate after the change of cutting conditions is predicted and the optimum conditions are finally selected for a case study.

引用

页码：374 / 379

页数：6

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