Journal
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
Volume 25, Issue 1, Pages 400-415Publisher
ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
DOI: 10.1016/j.ymssp.2010.07.014
Keywords
Data mining; Vibration signal; Singular spectrum analysis; Tool condition monitoring
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Funding
- Belgian Technical Cooperation (BTC)
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This paper explores the use of data mining techniques for tool condition monitoring in metal cutting. Pseudo-local singular spectrum analysis (SSA) is performed on vibration signals measured on the toolholder. This is coupled to a band-pass filter to allow definition and extraction of features which are sensitive to tool wear. These features are defined, in some frequency bands, from sums of Fourier coefficients of reconstructed and residual signals obtained by SSA. This study highlights two important aspects: strong relevance of information in high frequency vibration components and benefits of the combination of SSA and band-pass filtering to get rid of useless components (noise). (C) 2010 Elsevier Ltd. All rights reserved.
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