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.

Research on Thermal Error Modeling of CNC Machine Tool

2010 ◽  
Vol 135 ◽  
pp. 170-173 ◽  
Author(s):  
Qian Jian Guo ◽  
Jian Guo Yang
Keyword(s):  
Machine Tool ◽  
Back Propagation ◽  
Thermal Error ◽  
Back Propagation Neural Network ◽  
Error Modeling ◽  
Cnc Machine Tool ◽  
Cnc Machine ◽  
Daily Production ◽  
Proposed Model ◽  
Thermal Error Model

Four key temperature points of a CNC machine tool were obtained in this paper, and a thermal error model based on the four key temperature points was proposed by using based back propagation neural network. A thermal error compensation system was developed based on the proposed model, and which has been applied to the CNC machine tool in daily production. The results show that the thermal error in workpiece diameter has been reduced from 33 to 6 .

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 Compensating of Motorized Spindle Based on Improved Neural Network

2010 ◽  
Vol 129-131 ◽  
pp. 556-560 ◽  
Author(s):  
Chun Li Lei ◽  
Zhi Yuan Rui
Keyword(s):  
Neural Network ◽  
High Speed ◽  
Thermal Deformation ◽  
Influence Factors ◽  
Thermal Error ◽  
Error Modeling ◽  
Motorized Spindle ◽  
Key Factor ◽  
Manufacturing Accuracy ◽  
Thermal Error Model

In a lot of factors, thermal deformation of motorized high-speed spindle is a key factor affecting the manufacturing accuracy of machine tool. In order to reduce the thermal errors, the reasons and influence factors are analyzed. A thermal error model, that considers the effect of thermodynamics and speed on the thermal deformation, is proposed by using genetic algorithm-based radial basis function neural network. The improved neural network has been trained and tested, then a thermal error compensation system based on this model is established to compensate thermal deformation. The experiment results show that there is a 79% decrease in motorized spindle errors and this model has high accuracy.

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.

Modeling and Compensation of the Thermal Error on Feed Drive System of CNC Grinding Machine

2016 ◽  
Vol 679 ◽  
pp. 19-22
Author(s):  
W.C. Peng ◽  
Su Juan Wang ◽  
Hong Jian Xia
Keyword(s):  
Thermal Deformation ◽  
Back Propagation ◽  
Thermal Error ◽  
Back Propagation Neural Network ◽  
Drive System ◽  
Machining Accuracy ◽  
Feed Drive ◽  
Linear Encoder ◽  
Thermal Error Model ◽  
Feed Drive System

Thermal errors cause serious dimensional errors to a workpiece in precision machining. A feed drive system generates more heat through friction at contact areas, such as the Linear encoder and the guide, thereby causing thermal expansion which affects machining accuracy. Therefore, the thermal deformation of a Linear encoder is one of the most important objects to consider for high-accuracy machine tools. This paper analyzes the increase of the temperature and the thermal deformation of a Linear encoder feed drive system. During temperature variation is measured by using thermocouples , meanwhile, the thermal error of the guide is measured by a laser interferometer. A thermal error model is proposed in this study by using back propagation neural network (BPN). An experiment is carried out to verify the thermal error of the guide under different feed rates and environmental temperature.

Application of PPR to Thermal Error Modeling of an INDEX-G200 Turning Center

2011 ◽  
Vol 189-193 ◽  
pp. 4145-4148
Author(s):  
Qian Jian Guo ◽  
Lei He ◽  
Guang Ming Zhu
Keyword(s):  
Error Compensation ◽  
Projection Pursuit ◽  
Thermal Error ◽  
Cost Effective ◽  
Error Modeling ◽  
Thermal Errors ◽  
Turning Center ◽  
Compensation Technique ◽  
Dimensional Errors ◽  
Thermal Error Model

Thermal errors are the major contributor to the dimensional errors of a workpiece in precision machining. Error compensation technique is a cost-effective way to reduce thermal errors. Accurate modeling of errors is a prerequisite of error compensation. In this paper, a thermal error model was proposed by using projection pursuit regression (PPR). The PPR method improves the prediction accuracy of thermal deformation in the CNC turning center.

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