A statistical analysis of acoustic emission signals for tool condition monitoring (Articolo in rivista)

Type
Label
  • A statistical analysis of acoustic emission signals for tool condition monitoring (Articolo in rivista) (literal)
Anno
  • 2003-01-01T00:00:00+01:00 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
  • 10.1121/1.1532370 (literal)
Alternative label
  • G. Pontuale; F.A. Farrelly; A. Petri; L. Pitolli (2003)
    A statistical analysis of acoustic emission signals for tool condition monitoring
    in Acoustics research letters online
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • G. Pontuale; F.A. Farrelly; A. Petri; L. Pitolli (literal)
Pagina inizio
  • 13 (literal)
Pagina fine
  • 18 (literal)
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  • Published online 14 novembre 2002 (literal)
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  • http://scitation.aip.org/content/asa/journal/arlo/4/1/10.1121/1.1532370 (literal)
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  • ARLO_4 (literal)
Rivista
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  • Rivista dell'Acoustical Society of America (literal)
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  • 6 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroFascicolo
  • 1 (literal)
Note
  • ISI Web of Science (WOS) (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • CNR, Istituto di Acustica \"O.M. Corbino\", via del Fosso del Cavaliere, 00133 Roma, Italy (literal)
Titolo
  • A statistical analysis of acoustic emission signals for tool condition monitoring (literal)
Abstract
  • The statistical properties of acoustic emission signals for tool condition monitoring (TCM) applications in mechanical lathe machining are analyzed in this paper. Time series data and root mean square (RMS) values at various tool wear levels are shown to exhibit features that can be put into relation with ageing in both cases. In particular, the histograms of raw data show power-law distributions above a cross-over value, in which newer cutting tools exhibit more numerous larger events compared with more worn-out ones. For practical purposes, statistics based on RMS values are more feasible, and the analysis of these also reveals discriminating age-related features. The assumption that experimental RMS histograms follow a Beta (beta) distribution has also been tested. The residuals of the modeling beta functions indicate that the search for a more appropriate fitting function for the experimental distribution is desirable. (literal)
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