Adaptive tool condition monitoring system: A brief review

被引：13

作者：

Swain, Samarjit ^{[1
]}

Panigrahi, Isham ^{[1
]}

Sahoo, Ashok Kumar ^{[1
]}

Panda, Amlana ^{[1
]}

机构：

[1] KIIT, Sch Mech Engn, Bhubaneswar 24, Odisha, India

来源：

MATERIALS TODAY-PROCEEDINGS | 2020年 / 23卷

关键词：

Adaptive; Machining; Vibration; Tool condition monitoring; Measurement; AE signal; SURFACE-ROUGHNESS; CUTTING PARAMETERS; ACOUSTIC-EMISSION; NEURAL-NETWORKS; WEAR; OPERATIONS; VIBRATION; ONLINE; PREDICTION; TEMPERATURE;

D O I：

10.1016/j.matpr.2019.05.386

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

The increasing demand for manufacturing and scientific exploration is the process automation that leads to the broad research area in online monitoring during the machining operation. Keeping this in view, online tool monitoring the newer concept has been introduced to monitor the tool wear during the machining process. Additionally, an extensive study has been performed globally regarding adaptive tool monitoring system. With proper selection of monitoring technique, the machine tool damages scrapped parts and downtime can be circumvented. This paper presents a concise outline of tool condition monitoring and decision-making tools in the various machining process. (C) 2019 Elsevier Ltd. All rights reserved.

引用

页码：474 / 478

页数：5

共 41 条

[1] Surface roughness prediction based on cutting parameters and tool vibrations in turning operations [J].