Application of a Bayesian Network to Thermal Error Modeling and Analysis for Machine Tool

Abstract:

Article Preview

CNC machine tool dynamic thermal error compensation has always been a hot issue to improving precision. This dissertation proposes a method of machine tool thermal error modeling during processing, based on Bayesian network theory, by describing the correlation between the various factors of generated the heat error, through the sample data, analyzed and simplified the intrinsic correlation between these various factors, established the basic thermal error compensation model, and used the network’s good characteristic of self-studying, combining the result of update collection data, continually modify the model to reflect the machining process condition changes. Finally, the experimental results show the feasibility of Bayesian network model, it was a stronger application for achieving the thermal error compensation.

Info:

Periodical:

Edited by:

Bo Zhao, Guanglin Wang, Wei Ma, Zhibo Yang and Yanyan Yan

Pages:

616-620

DOI:

10.4028/www.scientific.net/KEM.455.616

Citation:

X. Li et al., "Application of a Bayesian Network to Thermal Error Modeling and Analysis for Machine Tool", Key Engineering Materials, Vol. 455, pp. 616-620, 2011

Online since:

December 2010

Authors:

Export:

Price:

$35.00

In order to see related information, you need to Login.

In order to see related information, you need to Login.