A cyber physical system for tool condition monitoring using electrical power and a mechanistic model-Reference-Cited by-同舟云学术

A cyber physical system for tool condition monitoring using electrical power and a mechanistic model

Published:2020-06 Issue: Volume:118 Page:103223
ISSN:0166-3615
Container-title:Computers in Industry
language:en
Short-container-title:Computers in Industry

Author:

Goodall Paul,Pantazis Dimitrios,West Andrew

Funder

Engineering and Physical Science Research Council

Publisher

Elsevier BV

Subject

General Engineering,General Computer Science

Reference27 articles.

1. A comparative study of using spindle motor power and eddy current for the detection of tool conditions in milling processes;Abbass;Proc. 2015 IEEE Int. Conf. Ind. Inf. INDIN 2015,2015

2. A review of machining monitoring systems based on artificial intelligence process models;Abellan-Nebot;Int. J. Adv. Manuf. Technol.,2010

3. Use of electrical power for online monitoring of tool condition;Al-Sulaiman;J. Mater. Process. Technol.,2005

4. Manufacturing Automation; Metal Cutting Mechanics, Machine Tool Vibrations and CNC Design;Altintas,2000

5. Tool condition monitoring system: a review;Ambhore;Mater. Today Proc.,2015

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