Support Vector Machines Model for Classification of Thermal Error in Machine Tools

This paper addresses a change in the concept of machine tool thermal error prediction which has been hitherto carried out by directly mapping them with the temperature of critical elements on the machine. The model developed herein using support vector machines, a powerful data-training algorithm, seeks to account for the impact of specific operating conditions, in addition to temperature variation, on the effective prediction of thermal errors. Several experiments were conducted to study the error pattern, which was found to change significantly with variation in operating conditions. This model attempts to classify the error based on operating conditions. Once classified, the error is then predicted based on the temperature states. This paper also briefly describes the concept of the implementation of such a comprehensive model along with an on-line error assessment and calibration system in a PC-based open-architecture controller environment, so that it could be employed in regular production for the purpose of periodic calibration of machine tools.

[1]  Günter Spur,et al.  Thermal Behaviour Optimization of Machine Tools , 1988 .

[2]  Bernhard Schölkopf,et al.  A tutorial on support vector regression , 2004, Stat. Comput..

[3]  Jun Ni,et al.  An On-Line Measurement Technique for Machine Volumetric Error Compensation , 1993 .

[4]  Alice E. Smith,et al.  Bias and variance of validation methods for function approximation neural networks under conditions of sparse data , 1998, IEEE Trans. Syst. Man Cybern. Part C.

[5]  F. Girosi,et al.  Nonlinear prediction of chaotic time series using support vector machines , 1997, Neural Networks for Signal Processing VII. Proceedings of the 1997 IEEE Signal Processing Society Workshop.

[6]  Raghunath Venugopal THERMAL EFFECTS ON THE ACCURACY OF NUMERICALLY CONTROLLED MACHINE TOOLS (NUMERICAL METHODS, EXPERIMENTAL) , 1985 .

[7]  Aun-Neow Poo,et al.  Error compensation in machine tools — a review: Part I: geometric, cutting-force induced and fixture-dependent errors , 2000 .

[8]  J. Nazuno Haykin, Simon. Neural networks: A comprehensive foundation, Prentice Hall, Inc. Segunda Edición, 1999 , 2000 .

[9]  Vladimir Vapnik,et al.  An overview of statistical learning theory , 1999, IEEE Trans. Neural Networks.

[10]  Simon Haykin,et al.  An explicit algorithm for training support vector machines , 1999, IEEE Signal Processing Letters.

[11]  L. Kops,et al.  A New Method for Determining the Thermal Contact Resistance at Machine Tool Joints , 1981 .

[12]  P. A. McKeown,et al.  Reduction and compensation of thermal errors in machine tools , 1995 .

[13]  Robert G. Wilhelm,et al.  Part Form Errors Predicted from Machine Tool Performance Measurements , 1997 .

[14]  Simon Haykin,et al.  Neural Networks: A Comprehensive Foundation , 1998 .

[15]  Jerzy Jedrzejewski,et al.  A new approach to modelling thermal behaviour of a machine tool under service conditions , 1992 .

[16]  Jenq-Shyong Chen,et al.  Real-time compensation of time-variant volumetric error on a machining center. , 1993 .

[17]  F. Jovane,et al.  Reconfigurable Manufacturing Systems , 1999 .

[18]  Nello Cristianini,et al.  An Introduction to Support Vector Machines and Other Kernel-based Learning Methods , 2000 .

[19]  Mohamed A. Elbestawi,et al.  A Strategy for the Compensation of Errors in Five-Axis Machining , 1995 .

[20]  Jerzy Jedrzejewski,et al.  Numerical Optimization of Thermal Behaviour of Machine Tools , 1990 .

[21]  Janet M. Twomey,et al.  Validation and Verification , 1997 .

[22]  Jun Ni,et al.  CNC Machine Accuracy Enhancement Through Real-Time Error Compensation , 1997 .

[23]  Aun-Neow Poo,et al.  Error compensation in machine tools — a review: Part II: thermal errors , 2000 .

[24]  S. Gunn Support Vector Machines for Classification and Regression , 1998 .

[25]  Alexander J. Smola,et al.  Support Vector Method for Function Approximation, Regression Estimation and Signal Processing , 1996, NIPS.

[26]  James B. Bryan,et al.  International Status of Thermal Error Research (1990) , 1990 .