Embedded tool condition monitoring for intelligent machining

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
Citation:	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

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