Please use this identifier to cite or link to this item: https://doi.org/10.1504/IJCAT.2007.012334
Title: Embedded tool condition monitoring for intelligent machining
Authors: Li, H.
Chen, X.
Zeng, H.
Li, X. 
Keywords: Embedded system
Intelligent machining
Milling
TCM
Tool condition monitoring
Issue Date: 2007
Source: Li, H.,Chen, X.,Zeng, H.,Li, X. (2007). Embedded tool condition monitoring for intelligent machining. International Journal of Computer Applications in Technology 28 (1) : 74-81. ScholarBank@NUS Repository. https://doi.org/10.1504/IJCAT.2007.012334
Abstract: In precision machining processes, major problems can be related to the conditions of the cutting tools. Online Tool Condition Monitoring (TCM) is hence of great industrial interest. An embedded Tool Condition Monitoring (eTCM) system is proposed to empower the machining system with adaptivity and intelligence. The eTCM takes aim at online detection of machining process abnormities such as tool breaking, chatter, etc. It employs multiple sensors including accelerometer, Acoustic Emission (AE) sensor and dynamometer to monitor an end milling process in an early phase study. The monitoring strategy, hardware architecture, monitoring algorithms and results are introduced and discussed in this paper. Copyright © 2007 Inderscience Enterprises Ltd.
Source Title: International Journal of Computer Applications in Technology
URI: http://scholarbank.nus.edu.sg/handle/10635/60160
ISSN: 09528091
DOI: 10.1504/IJCAT.2007.012334
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

SCOPUSTM   
Citations

6
checked on Dec 12, 2017

Page view(s)

16
checked on Dec 15, 2017

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.