AUTO-REGRESSIVE SVD ALGORITHMS AND CUTTING STATE IDENTIFICATION

Autor:	D.K. Anand, J.A. Manzari, B.S. Berger, C. Belai
Rok vydání:	2001
Předmět:	Acoustics and Ultrasonics Cutting tool Mechanical Engineering Numerical analysis System identification Condensed Matter Physics Singular value Machining Autoregressive model Mechanics of Materials Singular value decomposition Algorithm Parametric statistics Mathematics
Zdroj:	Journal of Sound and Vibration. 248:351-370
ISSN:	0022-460X
DOI:	10.1006/jsvi.2001.3757
Popis:	Functions of the singular values of matrices of third order cumulants associated with the TOR, CTOM and OARM algorithms for parametric bispectral estimation are shown to identify cutting states associated with the orthogonal cutting of stiff cylinders. Test functions and experimentally measured cutting tool accelerations are examined. Algorithms for auto-regressive approximations utilizing cumulants of arbitrary order are shown to characterize cubically phase-coupled test functions.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::27ebec5b2133b28850b57dbd2f9e9d9d https://doi.org/10.1006/jsvi.2001.3757 Zobrazit plný text záznamu Full Text from ScienceDirect