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Titolo:
Statistical optimization and assessment of a thermal error model for CNC machine tools
Autore:
Lee, JH; Yang, SH;
Indirizzi:
Kyungpook Natl Univ, Dept Mech Engn, Taegu 702701, South Korea Kyungpook Natl Univ Taegu South Korea 702701 , Taegu 702701, South Korea
Titolo Testata:
INTERNATIONAL JOURNAL OF MACHINE TOOLS & MANUFACTURE
fascicolo: 1, volume: 42, anno: 2002,
pagine: 147 - 155
SICI:
0890-6955(200201)42:1<147:SOAAOA>2.0.ZU;2-4
Fonte:
ISI
Lingua:
ENG
Soggetto:
ACCURACY ENHANCEMENT; COMPENSATION;
Keywords:
thermal error model; correlation grouping; regression analysis; multi-collinearity; judgement function; robustness;
Tipo documento:
Article
Natura:
Periodico
Settore Disciplinare:
Engineering, Computing & Technology
Citazioni:
12
Recensione:
Indirizzi per estratti:
Indirizzo: Yang, SH Kyungpook Natl Univ, Dept Mech Engn, Taegu 702701, South Korea Kyungpook Natl Univ Taegu South Korea 702701 02701, South Korea
Citazione:
J.H. Lee e S.H. Yang, "Statistical optimization and assessment of a thermal error model for CNC machine tools", INT J MACH, 42(1), 2002, pp. 147-155

Abstract

The objective of a thermal error compensation system for CNC machine toolsis improved machining accuracy through real time error compensation. The compensation capability depends on the accuracy of the thermal error model. A thermal error model can be obtained using an appropriate combination of temperature variables. In this study, the thermal error modeling is based ona correlation grouping and a successive linear regression analysis. Duringthe successive regression analysis, the residual mean square is minimized using a judgement function, which, although simple, is effective in the selection of variables in the error model. When evaluating the proposed thermal error model, the multi-collinearity problem and computational time are both improved through the correlation grouping, and the linear model is more robust against measurement noises than the engineering judgement model, which includes variables with higher order terms. The modeling method used in this study can be effectively and practically applied to real-time error compensation because it includes the advantages of simple application, reduced computational time, sufficient model accuracy, and model robustness. (C) 2001 Elsevier Science Ltd. All rights reserved.

ASDD Area Sistemi Dipartimentali e Documentali, Università di Bologna, Catalogo delle riviste ed altri periodici
Documento generato il 21/09/20 alle ore 12:26:04