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

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.

2009 ◽  
Vol 416 ◽  
pp. 401-405
Author(s):  
Qian Jian Guo ◽  
Xiao Ni Qi

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.


2010 ◽  
Vol 97-101 ◽  
pp. 3211-3214 ◽  
Author(s):  
Xiu Shan Wang ◽  
Yan Li ◽  
Yong Chang Yu

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.


2014 ◽  
Vol 75 (5-8) ◽  
pp. 933-946 ◽  
Author(s):  
Shibin Yin ◽  
Yin Guo ◽  
Yongjie Ren ◽  
Jigui Zhu ◽  
Shourui Yang ◽  
...  

2007 ◽  
Vol 359-360 ◽  
pp. 210-214 ◽  
Author(s):  
Xiu Shan Wang ◽  
Jian Guo Yang ◽  
Hao Wu ◽  
Jia Yu Yan

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.


2014 ◽  
Vol 945-949 ◽  
pp. 1669-1672
Author(s):  
Jun Sun ◽  
Xing Liu ◽  
Zhi Xuan Li

Aiming to deal with thermal error of NC machine tool which can cause reduce of machining accuracy, this paper uses an external error compensation which interacts with NC controllers and PMAC multi-axis and then revises the tool path by adding the error tested in real-time by PMAC card. The processing accuracy is improved eventually. This method can compensate machine geometric errors and thermal errors in real-time. Comparing with other methods of error preventing, this method is more effective and affordable.


2013 ◽  
Vol 431 ◽  
pp. 132-136
Author(s):  
Ji Zhu Liu ◽  
Wei Wei Yang ◽  
Yang Jun Wang ◽  
Tao Chen ◽  
Ming Qiang Pan ◽  
...  

In the technology of thermal error compensation in positioning platform with large trip and high precision, selecting the temperature measurement points rationally is particular important for successfully establishing the model of compensation. The method uses simulation to track platform heat distribution and thermal deformation under various thermal conditions. Temperature variables are grouped by different surfaces of the platform. Then a degree of grey incidence from grey system theory is introduced to identify the key temperature measurement points of each surface. Through the experiment data of thermal stress coupling analysis on the platform, the degree of correlation between all temperature measurement points and thermal displacement can be solved. The key temperature measurement points are confirmed by the largest value of the degree of correlation of each surface.


2014 ◽  
Vol 6 ◽  
pp. 1981-1988 ◽  
Author(s):  
T. Narendra Reddy ◽  
V. Shanmugaraj ◽  
Vinod Prakash ◽  
S. Gopi Krishna ◽  
S. Narendranath ◽  
...  

2007 ◽  
Vol 359-360 ◽  
pp. 569-573 ◽  
Author(s):  
Qian Jian Guo ◽  
Jian Guo Yang ◽  
Xiao Ni Qi

In order to fulfill the thermal error modeling of precision abrasive machining, a neural networks model is presented through analyzing thermal error sources of the grinding machine, the structure and algorithm of the neural networks is expatiated then;And because of reasonable sample and systematical training, the accuracy of thermal error models is improved. The hardware system for thermal error compensation is proposed finally, and an experiment is accomplished on the grinding machine. The result shows thermal errors is reduced from 6μm to 1μm.


2012 ◽  
Vol 220-223 ◽  
pp. 333-338
Author(s):  
Peng Zheng ◽  
Ling Liu

The thermal error of direct driving type A/C axis CNC milling head in the practical processing is analyzed. Based on the theory of homogeneous coordinate transformation and small error hypothesis, the transformation matrixes between the coordinate system of kinematic pairs and the relationship between errors and compensations are obtained. The thermal error compensation model and the thermal error compensation system which embedded into the Siemens 840D system are established, and play an important role in increasing the processing accuracy.


Sign in / Sign up

Export Citation Format

Share Document