Analysis on the Thermal Error Compensation Model of Direct-Drive A/C Bi-Rotary Milling Head

2011 ◽  
Vol 87 ◽  
pp. 59-62
Author(s):  
Peng Zheng ◽  
Xin Bao ◽  
Fang Cui
Keyword(s):  
Machine Tool ◽  
Error Compensation ◽  
Thermal Deformation ◽  
Thermal Error ◽  
Direct Drive ◽  
Cnc Machine ◽  
Compensation Model ◽  
Axis Rotation ◽  
Thermal Error Compensation ◽  
Deformation Error

The thermal deformation error that is the biggest error of effecting the machining precision of Direct-drive A/C Bi-rotary Milling Head was narrated in brief. Based on the introduce of the study status on the thermal error compensation techniques of CNC Machine tool, the momentum of thermal deformation of Bi-rotary Milling Head was analyzed. According to the Trigonometric Relations in A/C axis rotation angle of Bi-rotary Milling Head and the momentum of thermal deformation in Bi-rotary Milling Head and -axis respectively, a thermal error compensation model was established to make the Machine tool to compensate for thermal errors in -axis.

Robustness of thermal error compensation model of CNC machine tool

2013 ◽  
Author(s):  
Xianli Lang ◽  
Enming Miao ◽  
Yayun Gong ◽  
Pengcheng Niu ◽  
Zhishang Xu
Keyword(s):  
Machine Tool ◽  
Error Compensation ◽  
Thermal Error ◽  
Cnc Machine Tool ◽  
Cnc Machine ◽  
Compensation Model ◽  
Thermal Error Compensation

Thermal Error Analysis and Compensation Technology for High Precision Aspheric Measuring Platform

2013 ◽  
Vol 712-715 ◽  
pp. 1571-1575
Author(s):  
Feng Yang ◽  
Qia Heng Tang ◽  
Yin Biao Guo
Keyword(s):  
Error Analysis ◽  
High Precision ◽  
Heat Balance ◽  
Error Compensation ◽  
Thermal Deformation ◽  
Thermal Error ◽  
Positioning Error ◽  
Compensation Model ◽  
Balance State ◽  
Thermal Error Compensation

In this paper, a thermal error analysis and compensation method for a high precision aspheric measuring platform driven by a linear motor system is presented. After analyzing the heat source of thermal deformation, the thermal deformation of guide is selected to be object, and the thermal analysis method of guide in heat balance state is proposed. According to the motor temperature at different positions, the thermal error curve of guide is obtained through simulation. Modeling the global positioning error of measuring platform and the compensation model of thermal error using polynomial fitting, the thermal error compensation experiments is implemented by applying compensation system of measuring platform's controller. The experimental results show that the maximum positioning error in heat balance state is reduced from 1.5μm to 0.7μm, which verify the validity of thermal error compensation model.

scholarly journals Thermal Error Compensation of Spindle System of Computer Numerically Controlled Machine Tools Through Experiments and Modeling

2020 ◽  
Vol 19 (4) ◽  
pp. 301-309
Author(s):  
Jianchen Wang ◽  
Tao Jiang ◽  
Junquan Shen ◽  
Junhao Dai ◽  
Zequan Pan ◽  
...  
Keyword(s):  
Machine Tool ◽  
Error Compensation ◽  
Machine Tools ◽  
Thermal Error ◽  
Local Optimum ◽  
Cnc Machine ◽  
Machining Error ◽  
Generalization Ability ◽  
Computer Numerically Controlled ◽  
Thermal Error Compensation

This paper attempts to solve the insufficient machining precision of computer numerically controlled (CNC) machine tools, which is induced by the thermal error of the spindle. Firstly, the relationship between machining error and thermal sensitive points was analyzed through experiments. On this basis, the backpropagation neural network (BPNN) was improved by particle swarm optimization (PSO). Next, the improved network (PSO-BPNN) was used to build a thermal error compensation (TCE) model for the spindle of machine tools. Taking VM-500T precision machine tool as the object, the temperature data were grouped through the optimization based on thermal imaging, grey relational analysis (GRA), and fuzzy clustering, to determine the temperature sensitive items that causes the thermal error. To speed up network convergence, the PSO algorithm was introduced to optimize the number of hidden layers and the number of hidden layer nodes of the BPNN, lifting the network from the local optimum trap. To enhance the generalization ability, the weights and thresholds of the BPNN were also improved by the PSO. After that, two TCE models were established for the spindle of the machine tool, respectively based on the original BPNN and PSO-BPNN. Contrastive experiments show that the PSO-BPNN TCE model achieved the better generalization ability, and improved the prediction accuracy of the machining error of the CNC machine tool.

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