Robustness Analysis of the Thermal Error Model for a CNC Machine Tool

2016 ◽  
Author(s):  
Xinpeng Zhu ◽  
Quan Liu ◽  
Xiaomei Zhang ◽  
Xuemei Jiang ◽  
Ping Lou
Keyword(s):  
Machine Tool ◽  
Robustness Analysis ◽  
Thermal Error ◽  
Error Model ◽  
Cnc Machine Tool ◽  
Cnc Machine ◽  
Thermal Error Model

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 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 .

scholarly journals Identification, development and testing of thermal error compensation model for a headstock assembly of CNC turning centre

2014 ◽  
Vol 3 (2) ◽  
pp. 113 ◽  
Author(s):  
Ramesh Babu ◽  
V.Prabhu Raja ◽  
J. Kanchana ◽  
Devara Venkata Krishna
Keyword(s):  
Machine Tool ◽  
Analysis Of Variance ◽  
Error Compensation ◽  
Machine Tools ◽  
Thermal Error ◽  
Error Model ◽  
Transient Temperature ◽  
Cnc Machine ◽  
Grey Correlation ◽  
Thermal Error Model

In CNC machine tools, transient temperature variation in the headstock assembly is the major contributors for spindle thermal error. The compensation of thermal error is critical for ensuring the accuracy of machine tool. The performance of an error compensation system depends largely on the accuracy and robustness of the thermal error model. In the present work, a robust thermal error model is developed for minimizing the error in lateral direction of the spindle which significantly influences the geometrical accuracy of the workpiece. Analysis-of-variance (ANOVA) is applied to the results of the experiments in determining the percentage contribution of each individual temperature key point against a stated level of confidence. Based on the analysis of existing approaches for thermal error modeling of machine tools, an approach of LASSO (least absolute shrinkage and selection operator) is proposed in order to avoid the multi collinearity problem. The proposed method is an innovative variable selection method to remove redundant or unimportant temperature key points in the linear thermal error model and minimize the residual sum of squares. The predictive error model is found to have better robustness and accuracy in comparison to the combination of grey correlation and step wise linear regression for error compensation of CNC lathe. Keywords: Analysis Of Variance (ANOVA), CNC Machine Tool, Grey Correlation Analysis (GCA), Headstock Assembly, LASSO Regression, Mean Absolute Deviation (MAD), Mean Square Error (MSE), Robustness, Standard Deviation (SD), Thermal Error.

Application of Ubiquitous Sensor Network in Collection and Analysis of CNC Machine Tool Processing Status Information

2010 ◽  
Vol 455 ◽  
pp. 621-624
Author(s):  
X. Li ◽  
Y.Y. Yu
Keyword(s):  
Machine Tool ◽  
Sensor Network ◽  
Machine Tools ◽  
Thermal Error ◽  
Development Trend ◽  
Cnc Machine Tools ◽  
Cnc Machine Tool ◽  
Cnc Machine ◽  
Status Information ◽  
The Development Trend

Because of the practical requirement of real-time collection and analysis of CNC machine tool processing status information, we discuss the necessity and feasibility of applying ubiquitous sensor network(USN) in CNC machine tools by analyzing the characteristics of ubiquitous sensor network and the development trend of CNC machine tools, and application of machine tool thermal error compensation based on USN is presented.

Improvement of forecasting robustness of time series model for thermal error on CNC machine tool

2016 ◽  
Vol 24 (10) ◽  
pp. 2480-2489 ◽  
Author(s):  
苗恩铭 MIAO En-ming ◽  
刘 义 LIU Yi ◽  
董云飞 DONG Yun-fei ◽  
陈维康 CHEN Wei-kang
Keyword(s):  
Time Series ◽  
Machine Tool ◽  
Thermal Error ◽  
Time Series Model ◽  
Cnc Machine Tool ◽  
Cnc Machine

Thermal error measurement of spindle for 5-axis CNC machine tool based on ball bar

2015 ◽  
Vol 23 (5) ◽  
pp. 1401-1408
Author(s):  
何振亚 HE Zhen-ya ◽  
傅建中 FU Jian-zhong ◽  
陈子辰 CHEN Zi-chen
Keyword(s):  
Machine Tool ◽  
Thermal Error ◽  
Error Measurement ◽  
Cnc Machine Tool ◽  
Cnc Machine ◽  
Ball Bar
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