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Cited 15 time in webofscience Cited 21 time in scopus
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Statistical tool breakage detection schemes based on vibration signals in NC milling SCIE SCOPUS

Title
Statistical tool breakage detection schemes based on vibration signals in NC milling
Authors
Jun, CHSuh, SH
Date Issued
1999-11
Publisher
PERGAMON-ELSEVIER SCIENCE LTD
Abstract
We develop a vibration sensor-based tool breakage detection system for NC milling operations. The system obtains the time-domain vibration signal from the sensor attached on the spindle bracket of our CNC machine and declares tool failures through the on-line monitoring schemes. For the on-line detection, our approach is to use the statistical process control methods where control limits or thresholds are automatically calculated independently of cutting conditions. The main thrust of this paper is to compare the performance of the proposed statistical process monitoring methods including the X-bar control scheme, the exponentially weighted moving average (EWMA) scheme, and the adaptive EWMA scheme. The performance of the control schemes are compared in terms of the type I and II errors calculated from the experiment data. (C) 1999 Elsevier Science Ltd. All rights reserved.
Keywords
NEURAL-NETWORK; FAILURE-DETECTION; OPERATIONS; SYSTEM
URI
https://oasis.postech.ac.kr/handle/2014.oak/20333
DOI
10.1016/S0890-6955(99)00028-0
ISSN
0890-6955
Article Type
Article
Citation
INTERNATIONAL JOURNAL OF MACHINE TOOLS & MANUFACTURE, vol. 39, no. 11, page. 1733 - 1746, 1999-11
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서석환SUH, SUK HWAN
엔지니어링 대학원
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