Dynamic Modeling for Machine Tool Thermal Error Compensation

2003 ◽  
Vol 125 (2) ◽  
pp. 245-254 ◽  
Author(s):  
Hong Yang ◽  
Jun Ni
Keyword(s):  
Machine Tool ◽  
Model Performance ◽  
Thermal Error ◽  
Error Model ◽  
Error Modeling ◽  
Thermal Error Modeling ◽  
Modeling Methodology ◽  
On Line ◽  
Thermal Error Model ◽  
Thermal Error Compensation

This paper proposes a new thermal error modeling methodology called the Dynamic Thermal Error Modeling which improves the accuracy and robustness of the machine tool thermal error model. The characteristics of the thermoelastic system are investigated from the dynamic system viewpoint. The pseudo-hysteresis effect is revealed to be the major factor causing poor robustness of the conventional static thermal error model. System identification theory is applied to build the dynamic thermal error model for machine tool thermal error on-line prediction. The modeling procedure for the linear Output Error (OE) model is illustrated using simulation work for both one-dimensional spindle and two-dimensional machine structure thermal deformations. Model performance evaluation through spindle experiments shows that the thermal error dynamic model has advantages over the conventional static model in terms of model accuracy and robustness.

Dynamic Modeling for Machine Tool Thermal Error Compensation

2001 ◽  
Author(s):  
Hong Yang ◽  
Jingxia Yuan ◽  
Jun Ni
Keyword(s):  
Machine Tool ◽  
Dynamic Model ◽  
Model Performance ◽  
Thermal Error ◽  
Error Model ◽  
Error Modeling ◽  
Thermal Error Modeling ◽  
Modeling Methodology ◽  
On Line ◽  
Thermal Error Model

Abstract This paper presents a new thermal error modeling methodology called the Dynamic Thermal Error Modeling which improves the accuracy and robustness of the machine tool thermal error model. The characteristics of the thermoelastic system are investigated from the dynamic system viewpoint. The pseudo-hysteresis effect is revealed to be the major factor causing poor robustness of the conventional static thermal error model. System identification theory is applied to build the dynamic model for machine tool thermal error on-line estimation. The modeling procedure for the linear Output Error (OE) model is illustrated using simulation work for both one-dimensional spindle and two-dimensional machine structure thermal deformations. Model performance evaluation through spindle experiments shows that the thermal error dynamic model has advantages over the static model in terms of model accuracy and robustness.

Clustering Regression Modeling for Gear Hobbing Machine Thermal Error Compensation

2009 ◽  
Vol 416 ◽  
pp. 401-405
Author(s):  
Qian Jian Guo ◽  
Xiao Ni Qi
Keyword(s):  
Error Compensation ◽  
Thermal Error ◽  
Regression Modeling ◽  
Error Model ◽  
Error Modeling ◽  
Machining Accuracy ◽  
Thermal Error Modeling ◽  
Gear Hobbing ◽  
Thermal Error Model ◽  
Thermal Error Compensation

This paper proposes a new thermal error modeling methodology called Clustering Regression Thermal Error Modeling which not only improves the accuracy and robustness but also saves the time and cost of gear hobbing machine thermal error model. The major heat sources causing poor machining accuracy of gear hobbing machine are investigated. Clustering analysis method is applied to reduce the number of temperature sensors. Least squares regression modeling approach is used to build thermal error model for thermal error on-line prediction of gear hobbing machine. Model performance evaluation through thermal error compensation experiments shows that the new methodology has the advantage of higher accuracy and robustness.

Real Time Thermal Error Modeling and Compensation of 5-Axis NC Grinding Machine Tool

2007 ◽  
Vol 359-360 ◽  
pp. 210-214 ◽  
Author(s):  
Xiu Shan Wang ◽  
Jian Guo Yang ◽  
Hao Wu ◽  
Jia Yu Yan
Keyword(s):  
Machine Tool ◽  
Real Time ◽  
Thermal Error ◽  
Error Modeling ◽  
Volumetric Error ◽  
Sensing System ◽  
Grinding Machine ◽  
Thermal Error Model ◽  
Thermal Error Compensation ◽  
Nc Grinding

The thermal error model of the 5-axis grinding machine tool was acquired by the homogeneous coordinate transformation, including 17 thermal error components. The thermal volumetric error real time compensation model was built by using the multiple regression analysis. The thermal error compensation control system and the temperature sensing system were developed and used as real-time compensation for the 5-axis grinding machine tool.

Thermal Error Modeling of a CNC Machine Tool

2013 ◽  
Vol 303-306 ◽  
pp. 1782-1785
Author(s):  
Chong Zhi Mao ◽  
Qian Jian Guo
Keyword(s):  
Machine Tool ◽  
Back Propagation ◽  
Thermal Error ◽  
Error Modeling ◽  
Machining Accuracy ◽  
Cnc Machine Tool ◽  
Cnc Machine ◽  
Thermal Error Modeling ◽  
Thermal Errors ◽  
Thermal Error Model

The purpose of this research is to improve the machining accuracy of a CNC machine tool through thermal error modeling and compensation. In this paper, a thermal error model based on back propagation networks (BPN) is presented, and the compensation is fulfilled. The results show that the BPN model improves the prediction accuracy of thermal errors on the CNC machine tool, and the thermal drift has been reduced from 15 to 5 after compensation.

Robust Machine Tool Thermal Error Modeling Through Thermal Mode Concept

2008 ◽  
Vol 130 (6) ◽  
Author(s):  
Jie Zhu ◽  
Jun Ni ◽  
Albert J. Shih
Keyword(s):  
Machine Tool ◽  
Thermal Error ◽  
Error Modeling ◽  
Thermal Mode ◽  
Thermal Error Modeling ◽  
Thermal Errors ◽  
Underlying Mechanisms ◽  
Modeling Strategy ◽  
Thermal Error Compensation ◽  
Insight Into

Thermal errors are among the most significant contributors to machine tool errors. Successful reduction in thermal errors has been realized through thermal error compensation techniques in the past few decades. The effectiveness of thermal error models directly determines the compensation results. Most of the current thermal error modeling methods are empirical and highly rely on the collected data under specific working conditions, neglecting the insight into the underlying mechanisms that result in thermal deformations. In this paper, an innovative temperature sensor placement scheme and thermal error modeling strategy are proposed based on the thermal mode concept. The modeling procedures for both position independent and position dependent thermal errors are illustrated through numerical simulation and experiments. Satisfactory results have been achieved in terms of model accuracy and robustness.

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

2010 ◽  
Vol 455 ◽  
pp. 616-620
Author(s):  
X. Li ◽  
Q. Lei ◽  
Z.H. Li
Keyword(s):  
Machine Tool ◽  
Bayesian Network ◽  
Error Compensation ◽  
Process Condition ◽  
Thermal Error ◽  
Error Modeling ◽  
Machining Process ◽  
Cnc Machine ◽  
Thermal Error Modeling ◽  
Thermal Error Compensation

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.

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