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.

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.

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.

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.

Thermal Error Modeling and Prediction of a Heavy Floor-Type Milling and Boring Machine Tool

2015 ◽  
Author(s):  
Fengchun Li ◽  
Tiemin Li ◽  
Haitong Wang
Keyword(s):  
Boundary Conditions ◽  
Machine Tool ◽  
Superposition Principle ◽  
Engineering Application ◽  
Thermal Error ◽  
Error Modeling ◽  
Simulation Data ◽  
Thermal Error Modeling ◽  
Fea Model ◽  
Modeling And Prediction

Thermal error modeling and prediction of a heavy floor-type milling and boring machine tool was studied in this paper. An FEA model and a thermal network of the machine tool’s ram was established. The influence of boundary conditions on thermal error was studied to find out the boundary conditions that needn’t to be calculated precisely, reducing the time cost of the work. Superposition principle of heat sources was used in the FEA to get the simulation data of thermal error and temperature. A model based on the simulation data was established to predict the thermal error during the work process. An experiment was performed to verify the accuracy of the model. The result shows that the model accuracy is 87%. The method in this paper is expected to be used in engineering application.

Monitoring and Compensation of Thermal Error of Profile Grinding Spindle

2007 ◽  
Vol 359-360 ◽  
pp. 219-223
Author(s):  
Li Ming Xu ◽  
Lun Shi ◽  
Xiao Ming Zhao ◽  
De Jin Hu
Keyword(s):  
Error Compensation ◽  
Thermal Deformation ◽  
Thermal Error ◽  
Temperature Sensors ◽  
Error Modeling ◽  
Support Vector ◽  
Thermal Error Modeling ◽  
Profile Grinding ◽  
On Line ◽  
The Relationship

Spindle thermal deformation is the main error source of many precision profile grinders. In this paper, the relationship between spindle temperature and either radial or axial thermal deformation is studied based on experiments. The placement and amount of temperature sensors are optimized. Then a kind of thermal error modeling method based on support vector machine is presented and applied in the modeling of thermal error of profile grinding. The result shows the model is robust and the on-line accurate prediction of grinding thermal error is realized based on monitoring of temperature rise of spindle. Finally, the error compensation strategy is discussed for further application of thermal error modeling.

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.

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