Neural-networks-based tool wear monitoring in turning medium carbon steel using a coated carbide tool

被引：30

作者：

Das, S ^{[1
]}

Bandyopadhyay, PP ^{[1
]}

Chattopadhyay, AB ^{[1
]}

机构：

[1] INDIAN INST TECHNOL,DEPT MECH ENGN,KHARAGPUR 721302,W BENGAL,INDIA

来源：

JOURNAL OF MATERIALS PROCESSING TECHNOLOGY | 1997年 / 63卷 / 1-3期

关键词：

turning; tool wear; cutting force; vibration; neural networks; sensor fusion; on-line monitoring;

D O I：

10.1016/S0924-0136(96)02622-2

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

Appropriate on-line tool condition monitoring is essential for sophisticated and automated modern machine tools for aiding better tool management It enables higher productivity and safety to the machine-fixture-tool-work system. This paper presents a neural-networks- based system for on-line assessment of TiN-coated carbide inserts. The wear estimates by the system are observed to have very close agreement with the directly measured flank wear.

引用

页码：187 / 192

页数：6

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