Authors: Huaizhong Li, Xiaoqi Chen, Hao Zeng, Xiaoping Li
Addresses: Mechatronics Group, Singapore Institute of Manufacturing Technology, 71 Nanyang Drive, 638075, Singapore. ' Mechatronics Group, Singapore Institute of Manufacturing Technology, 71 Nanyang Drive, 638075, Singapore. ' Manufacturing Execution and Control (MEC) Group, Singapore Institute of Manufacturing Technology, 71 Nanyang Drive, 638075, Singapore. ' Department of Mechanical Engineering, The National University of Singapore, 9 Engineering Drive 1, 117576, Singapore
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 an 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.
Keywords: tool condition monitoring; TCM; milling; intelligent machining; embedded systems; cutting tools; monitoring.
International Journal of Computer Applications in Technology, 2007 Vol.28 No.1, pp.74 - 81
Published online: 06 Feb 2007 *Full-text access for editors Access for subscribers Purchase this article Comment on this article