Thermal Error Modeling of Machine Tools Based on M-RAN

2011 ◽  
Vol 121-126 ◽  
pp. 529-533
Author(s):  
Jian Han ◽  
Li Ping Wang ◽  
Ning Bo Cheng ◽  
Xu Wang
Keyword(s):  
Machine Tool ◽  
Eddy Current ◽  
Machine Tools ◽  
Thermal Error ◽  
Error Modeling ◽  
Test Results ◽  
Thermal Errors ◽  
Machining Center ◽  
Machining Errors ◽  
Minimal Resource

Thermal error in machine tools is one of the most significant causes of machining errors. This paper presents a new modeling method for machine tool error. Minimal-resource allocating networks (M-RAN) are used to establish the relationships between the temperature variables and thermal errors. Pt-100 thermal resistances and eddy current sensors are used to measure the temperature variables and the thermal errors respectively. A machining center is used to experiment. The test results show that method with minimal-resource allocating networks can predict the thermal errors of the machine accurately.

Numerical Analysis of Thermal Error for a 4-Axises Horizontal Machining Center

2017 ◽  
Vol 868 ◽  
pp. 64-68
Author(s):  
Yu Bin Huang ◽  
Wei Sun ◽  
Qing Chao Sun ◽  
Yue Ma ◽  
Hong Fu Wang
Keyword(s):  
Machine Tool ◽  
Working Condition ◽  
Prediction Method ◽  
Thermal Error ◽  
Error Modeling ◽  
Model Verification ◽  
Design Stage ◽  
Thermal Errors ◽  
Machining Center ◽  
Machining Errors

Thermal deformations of machine tool are among the most significant error source of machining errors. Most of current thermal error modeling researches is about 3-axies machine tool, highly reliant on collected date, which could not predict thermal errors in design stage. In This paper, in order to estimate the thermal error of a 4-axise horizontal machining center. A thermal error prediction method in machine tool design stage is proposed. Thermal errors in workspace in different working condition are illustrated through numerical simulation and volumetric error model. Verification experiments shows the outcomes of this prediction method are basically correct.

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.

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.

Research on Volumetric Error Measurement, Modeling and Compensation for NC Machine Tools

2014 ◽  
Vol 513-517 ◽  
pp. 4202-4205
Author(s):  
Hong Xin Zhang ◽  
Qian Jian Guo
Keyword(s):  
Machine Tool ◽  
Error Compensation ◽  
Machine Tools ◽  
Thermal Error ◽  
Error Modeling ◽  
Cnc Machine Tools ◽  
Machining Accuracy ◽  
Volumetric Error ◽  
The Impact ◽  
Thermal Error Compensation

With the increasing requirements of the machining accuracy of CNC machine tools, the impact of thermal deformation is growing. Thermal error compensation technology can predict and compensate the thermal errors in real-time, and improve the machining accuracy of the machine tool. In this paper, the research objects of thermal error compensation is expanded to the volumetric error of the machine tool, the volumetric error modeling of a three-axis machine tool is fulfilled and a compensator is developed for the compensation experiment, which provides scientific basis for the improvement of the machining accuracy.

Study on the Application of the Combined Prediction Modeling Method to Thermal Error Modeling on NC Machine Tools

2007 ◽  
Vol 329 ◽  
pp. 779-784 ◽  
Author(s):  
Y.X. Li ◽  
Jian Guo Yang ◽  
Yu Yao Li ◽  
H.T. Zhang ◽  
G. Turyagyenda
Keyword(s):  
Prediction Model ◽  
Machine Tool ◽  
Thermal Error ◽  
Error Modeling ◽  
Primary Data ◽  
Analysis Model ◽  
Grey System ◽  
Trend Prediction ◽  
Thermal Error Modeling ◽  
Thermal Errors

Due to the complexity of machine tool thermal errors affected by various factors, a new combining prediction model, based on the theory of gery system GM (1,1) model, is applied to the trend prediction of machine tool thermal errors. The degree of smoothness of primary data sequence is first improved by function transform method and sequentially grey system GM (1,1) model is established; second, time series analysis model is established by remnant sequence of GM (1,1) model to amend the precision of grey system GM (1,1) model. Thus, the precision of combining prediction model is further improved. Through the prediction study on thermal error modeling in a spot NC turning center, testing results showed that combining prediction model can highly improve machine tool’s prediction precision and make it more effective for real-time compensation of machine tool thermal error.

Thermal Error Robust Modeling and Real Time Compensation Based on the GA-BPN Theory on a Vertical Machine Centre

2010 ◽  
Vol 97-101 ◽  
pp. 3211-3214 ◽  
Author(s):  
Xiu Shan Wang ◽  
Yan Li ◽  
Yong Chang Yu
Keyword(s):  
Error Compensation ◽  
Thermal Error ◽  
Error Modeling ◽  
Machining Process ◽  
Field Analysis ◽  
Cnc Machine Tools ◽  
Thermal Errors ◽  
Machining Center ◽  
Thermal Error Model ◽  
Thermal Error Compensation

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.

Study on the Thermal Errors of CNC Machine Tools

2012 ◽  
Vol 472-475 ◽  
pp. 2918-2921
Author(s):  
Hong Qi Luo ◽  
Yue Hua Lai
Keyword(s):  
Machine Tools ◽  
Thermal Deformation ◽  
Thermal Error ◽  
External Heat ◽  
Cnc Machining ◽  
Cnc Machine Tools ◽  
Heat Sources ◽  
Cnc Machine ◽  
Thermal Errors ◽  
Machining Errors

Thermal deformation is produced by heat sources in CNC machine tools. Thermal error is one of the main parts in CNC machining errors. The internal and external heat sources were introduced. The research status about thermal errors was analyzed, including identification of thermal sensitive points, precaution against thermal errors and error compensation. Finally, thermal error models were summarized and discussed.

scholarly journals Application of the digital model thermal errors of machine tools in automated production

2021 ◽  
Vol 2094 (4) ◽  
pp. 042022
Author(s):  
V V Pozevalkin ◽  
A N Polyakov
Keyword(s):  
Neural Network ◽  
Machine Tool ◽  
Machine Tools ◽  
Polynomial Regression ◽  
Block Diagram ◽  
Thermal Error ◽  
External Input ◽  
Machine Model ◽  
Automated Production ◽  
Thermal Errors

Abstract The article presents a predicting method for a machine tool thermal error based on a nonlinear autoregressive neural network with an external input, as well as methods for smoothing experimental data obtained from measuring devices by approximation using polynomial regression and the gray systems theory. The development of accurate and robust thermal models is a critical step in achieving high productivity in thermal deformation reduction techniques on machine tools. Because thermal deformations of the machine structure caused by temperature increase often lead to thermal errors and reduce the accuracy of machining parts. The use of neural networks is a promising direction in solving forecasting problems. The authors propose a block diagram of a thermal process digital twin based on a neural network, which can be used in automated production. The results of the experiment carried out for the machine model 400V are obtained in the form of an assessment of approximation quality and accuracy of the forecasting model. The results show that the use of the proposed smoothing methods and a model for predicting a machine tool thermal error based on a neural network can improve the forecast accuracy.

Thermal Error Modeling and Compensation of a CNC Machining Center

2012 ◽  
Vol 490-495 ◽  
pp. 1516-1520
Author(s):  
Jian Han ◽  
Li Ping Wang ◽  
Lian Qing Yu ◽  
Hai Tong Wang
Keyword(s):  
Clustering Analysis ◽  
Error Compensation ◽  
Thermal Error ◽  
Error Modeling ◽  
Cnc Machining ◽  
Thermally Induced ◽  
Thermal Errors ◽  
Machining Center ◽  
Novel Approach ◽  
Cnc Machining Center

Error modeling and compensation is the most effective way to reduce thermal errors. In this paper, a novel approach to predict the thermal error of machine tool based on M-RAN is presented, clustering analysis is used to select the temperature variables, and then an easy and economical measurement system is applied to measure the temperature variables and thermal shift of CNC machining center. The thermally induced errors are estimated in real-time using the trained M-RAN network. The proposed approach is verified through error compensation test.

Sign in / Sign up

Export Citation Format

Share Document