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.

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.

Application of Clustering Regression to Thermal Error Modeling of NC Machine Tool

2010 ◽  
Vol 431-432 ◽  
pp. 110-113
Author(s):  
Xiao Ni Qi ◽  
Qian Jian Guo
Keyword(s):  
Clustering Analysis ◽  
Error Compensation ◽  
Thermal Error ◽  
Error Modeling ◽  
Nc Machine Tool ◽  
Thermal Errors ◽  
Gear Hobbing ◽  
Nc Machine ◽  
Thermal Error Model ◽  
Thermal Error Compensation

The thermal distortion of YK3610 hobbing machine is analyzed. The concept of clustering analysis is proposed and implemented on the gear hobbing machine. The model was used in the experimental of thermal error compensation. The results show that the thermal error compensation control system can reduce thermal errors significantly and the prediction accuracy of the thermal error model is high enough.

Application of ICA Method to Thermal Error Modeling of Gear Hobbing Machine

2007 ◽  
Vol 24-25 ◽  
pp. 309-314 ◽  
Author(s):  
Qian Jian Guo ◽  
Jian Guo Yang ◽  
Xiu Shan Wang
Keyword(s):  
Thermal Error ◽  
Error Modeling ◽  
Machining Accuracy ◽  
Single Chip ◽  
Single Chip Microcomputer ◽  
Thermal Error Modeling ◽  
Hardware System ◽  
Pitch Error ◽  
Gear Hobbing ◽  
Independent Component Analysis Method

Based on the synthetic analysis of thermal error sources, ICA (Independent component analysis) method is proposed to reduce the number of temperature sensor, and the selected temperature variables is used for thermal error modeling of gear hobbing machine. Finally, the hardware system of thermal error compensation is presented based on SCM (Single chip microcomputer) technique, and which is tested on Y3150K hobbing machine then. The results show that cumulative pitch error is reduced from 80μmto 20μm, and the machining accuracy is improved more than 2 grades.

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.

Research on Thermal Error Modeling of YK3610 Hobbing Machine

2012 ◽  
Vol 426 ◽  
pp. 293-296
Author(s):  
Qian Jian Guo ◽  
Jian Guo Yang
Keyword(s):  
Neural Network ◽  
Error Compensation ◽  
Back Propagation ◽  
Thermal Error ◽  
Back Propagation Neural Network ◽  
Error Modeling ◽  
Daily Production ◽  
Machine Error ◽  
Thermal Error Modeling ◽  
Thermal Error Model

Thermal error modeling. Neural network. Gear hobbing machine. Error compensation. Abstract. Four key thermal sources of YK3610 hobbing machine were selected in this paper, and a thermal error model based on the four temperature variables was proposed by using back propagation neural network. A thermal error compensation system was developed based on the proposed model, and which has been applied to the YK3610 hobbing machine in daily production. The result shows that the prediction accuracy of thermal deformation in the YK3610 hobbing machine has been improved.

Application of Autoregressive Distributed Lag (ADL) Model to Thermal Error Modeling on NC Machine Tools

2011 ◽  
Vol 103 ◽  
pp. 9-14 ◽  
Author(s):  
En Ming Miao ◽  
Xin Wang ◽  
Ye Tai Fei ◽  
Yan Yan
Keyword(s):  
Error Compensation ◽  
Machine Tools ◽  
Thermal Error ◽  
Error Modeling ◽  
Thermal Error Modeling ◽  
Distributed Lag ◽  
Autoregressive Distributed Lag ◽  
Nc Machine ◽  
Nc Machine Tools ◽  
Thermal Error Compensation

Thermal error modeling method is an important field of thermal error compensation on NC machine tools, it is also a key for improving the machining accuracy of machine tools. The accuracy of the model directly affects the quality of thermal error compensation. On the basis of multiple linear regression (MLR) model, this paper proposes an autoregressive distributed lag (ADL) model of thermal error and establishes an accurate ADL model by stepwise regression analysis. The ADL model of thermal error is established with measured data, it proved the ADL model is available and has a high accuracy on predicting thermal error by comparing with MLR models.

Research on Volumetric Error Measurement, Modeling and Compensation for NC Machine Tools

2014 ◽  
Vol 513-517 ◽  
pp. 4202-4205
Author(s):  
Hong Xin Zhang ◽  
Qian Jian Guo
Keyword(s):  
Machine Tool ◽  
Error Compensation ◽  
Machine Tools ◽  
Thermal Error ◽  
Error Modeling ◽  
Cnc Machine Tools ◽  
Machining Accuracy ◽  
Volumetric Error ◽  
The Impact ◽  
Thermal Error Compensation

With the increasing requirements of the machining accuracy of CNC machine tools, the impact of thermal deformation is growing. Thermal error compensation technology can predict and compensate the thermal errors in real-time, and improve the machining accuracy of the machine tool. In this paper, the research objects of thermal error compensation is expanded to the volumetric error of the machine tool, the volumetric error modeling of a three-axis machine tool is fulfilled and a compensator is developed for the compensation experiment, which provides scientific basis for the improvement of the machining accuracy.

Synthesis Error Modeling and Thermal Error Compensation of Five-Axis Machining Center

2006 ◽  
Vol 532-533 ◽  
pp. 49-52 ◽  
Author(s):  
Xiu Shan Wang ◽  
Jian Guo Yang ◽  
Qian Jian Guo
Keyword(s):  
Real Time ◽  
Error Compensation ◽  
Thermal Error ◽  
Error Model ◽  
Error Modeling ◽  
Thermal Displacement ◽  
Collector System ◽  
Machining Center ◽  
Five Axis ◽  
Thermal Error Compensation

The synthesis error model of UCP710 five-axis machining center is divided into two parts: the position and orientation error models, and the article gets their models which are used as real-time compensation. One data collector system of thermal displacement and temperature is developed and used as real-time compensation for UCP710. The results of thermal error compensation have proved that the error model is correct and collector system works well.

Thermal Error Robust Modeling and Real Time Compensation Based on the GA-BPN Theory on a Vertical Machine Centre

2010 ◽  
Vol 97-101 ◽  
pp. 3211-3214 ◽  
Author(s):  
Xiu Shan Wang ◽  
Yan Li ◽  
Yong Chang Yu
Keyword(s):  
Error Compensation ◽  
Thermal Error ◽  
Error Modeling ◽  
Machining Process ◽  
Field Analysis ◽  
Cnc Machine Tools ◽  
Thermal Errors ◽  
Machining Center ◽  
Thermal Error Model ◽  
Thermal Error Compensation

Thermal errors generally account for as much as 70% of the total errors of CNC machine tools, are the most contributor to the workpiece dimensional precision in precision machining process. Thermal error compensation is an effective way to decreasing thermal errors. Precision mode is a key to thermal error compensation. In this paper thermal error modeling method based on the artificial neural networks (ANN) algorithm is applied for a vertical machining center. Four key temperature points of a vertical machining center were obtained based on the temperature field analysis. A novel genetic algorism-Back propagation neural network (GA-BPN) thermal error model was proposed on the basis of four temperature points. The emulations and experiments prove that there was about a 60% increase in machine tool precision.

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.

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