Application of a Bayesian Network to Thermal Error Modeling and Analysis for Machine Tool

2010 ◽  
Vol 455 ◽  
pp. 616-620
Author(s):  
X. Li ◽  
Q. Lei ◽  
Z.H. Li
Keyword(s):  
Machine Tool ◽  
Bayesian Network ◽  
Error Compensation ◽  
Process Condition ◽  
Thermal Error ◽  
Error Modeling ◽  
Machining Process ◽  
Cnc Machine ◽  
Thermal Error Modeling ◽  
Thermal Error Compensation

CNC machine tool dynamic thermal error compensation has always been a hot issue to improving precision. This dissertation proposes a method of machine tool thermal error modeling during processing, based on Bayesian network theory, by describing the correlation between the various factors of generated the heat error, through the sample data, analyzed and simplified the intrinsic correlation between these various factors, established the basic thermal error compensation model, and used the network’s good characteristic of self-studying, combining the result of update collection data, continually modify the model to reflect the machining process condition changes. Finally, the experimental results show the feasibility of Bayesian network model, it was a stronger application for achieving the thermal error compensation.

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.

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.

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.

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.

Robust Machine Tool Thermal Error Modeling Through Thermal Mode Concept

2008 ◽  
Vol 130 (6) ◽  
Author(s):  
Jie Zhu ◽  
Jun Ni ◽  
Albert J. Shih
Keyword(s):  
Machine Tool ◽  
Thermal Error ◽  
Error Modeling ◽  
Thermal Mode ◽  
Thermal Error Modeling ◽  
Thermal Errors ◽  
Underlying Mechanisms ◽  
Modeling Strategy ◽  
Thermal Error Compensation ◽  
Insight Into

Thermal errors are among the most significant contributors to machine tool errors. Successful reduction in thermal errors has been realized through thermal error compensation techniques in the past few decades. The effectiveness of thermal error models directly determines the compensation results. Most of the current thermal error modeling methods are empirical and highly rely on the collected data under specific working conditions, neglecting the insight into the underlying mechanisms that result in thermal deformations. In this paper, an innovative temperature sensor placement scheme and thermal error modeling strategy are proposed based on the thermal mode concept. The modeling procedures for both position independent and position dependent thermal errors are illustrated through numerical simulation and experiments. Satisfactory results have been achieved in terms of model accuracy and robustness.

Sign in / Sign up

Export Citation Format

Share Document