Application of PPR to Thermal Error Modeling of an INDEX-G200 Turning Center

2011 ◽  
Vol 189-193 ◽  
pp. 4145-4148
Author(s):  
Qian Jian Guo ◽  
Lei He ◽  
Guang Ming Zhu
Keyword(s):  
Error Compensation ◽  
Projection Pursuit ◽  
Thermal Error ◽  
Cost Effective ◽  
Error Modeling ◽  
Thermal Errors ◽  
Turning Center ◽  
Compensation Technique ◽  
Dimensional Errors ◽  
Thermal Error Model

Thermal errors are the major contributor to the dimensional errors of a workpiece in precision machining. Error compensation technique is a cost-effective way to reduce thermal errors. Accurate modeling of errors is a prerequisite of error compensation. In this paper, a thermal error model was proposed by using projection pursuit regression (PPR). The PPR method improves the prediction accuracy of thermal deformation in the CNC turning center.

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.

Application of Clustering Regression to Thermal Error Modeling of NC Machine Tool

2010 ◽  
Vol 431-432 ◽  
pp. 110-113
Author(s):  
Xiao Ni Qi ◽  
Qian Jian Guo
Keyword(s):  
Clustering Analysis ◽  
Error Compensation ◽  
Thermal Error ◽  
Error Modeling ◽  
Nc Machine Tool ◽  
Thermal Errors ◽  
Gear Hobbing ◽  
Nc Machine ◽  
Thermal Error Model ◽  
Thermal Error Compensation

The thermal distortion of YK3610 hobbing machine is analyzed. The concept of clustering analysis is proposed and implemented on the gear hobbing machine. The model was used in the experimental of thermal error compensation. The results show that the thermal error compensation control system can reduce thermal errors significantly and the prediction accuracy of the thermal error model is high enough.

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.

Thermal Error Modeling and Compensation for an INDEX-G200 Turning Center

2011 ◽  
Vol 215 ◽  
pp. 53-55
Author(s):  
Qian Jian Guo ◽  
Lei He ◽  
Guang Ming Zhu
Keyword(s):  
Prediction Accuracy ◽  
Back Propagation ◽  
Thermal Error ◽  
Error Modeling ◽  
Thermal Drift ◽  
Thermal Error Modeling ◽  
Thermal Errors ◽  
Whole Process ◽  
Turning Center ◽  
Bp Model

The purpose of this research is to fulfill thermal error modeling and compensation of an INDEX-G200 turning center. This paper presents the whole process of thermal error modeling and compensation by using back propagation neural networks. Results show that the BP model improves the prediction accuracy of thermal errors on the turning center and the thermal drift has been reduced from 39 to 11 after compensation.

Research on Thermal Error Modeling of YK3610 Hobbing Machine

2012 ◽  
Vol 426 ◽  
pp. 293-296
Author(s):  
Qian Jian Guo ◽  
Jian Guo Yang
Keyword(s):  
Neural Network ◽  
Error Compensation ◽  
Back Propagation ◽  
Thermal Error ◽  
Back Propagation Neural Network ◽  
Error Modeling ◽  
Daily Production ◽  
Machine Error ◽  
Thermal Error Modeling ◽  
Thermal Error Model

Thermal error modeling. Neural network. Gear hobbing machine. Error compensation. Abstract. Four key thermal sources of YK3610 hobbing machine were selected in this paper, and a thermal error model based on the four temperature variables was proposed by using back propagation neural network. A thermal error compensation system was developed based on the proposed model, and which has been applied to the YK3610 hobbing machine in daily production. The result shows that the prediction accuracy of thermal deformation in the YK3610 hobbing machine has been improved.

Error Modeling and Compensation for High-Precision Non-Contact Four Coordinate Measuring System

2010 ◽  
Vol 437 ◽  
pp. 232-236 ◽  
Author(s):  
Fei Zhang ◽  
Zhuang De Jiang ◽  
Bing Li ◽  
Jian Jun Ding ◽  
Lei Chen
Keyword(s):  
High Precision ◽  
Error Compensation ◽  
Rotation Axis ◽  
Thermal Error ◽  
Geometric Error ◽  
Error Modeling ◽  
Measuring System ◽  
Precision Measuring ◽  
Compensation Methods ◽  
Compensation Technique

The error compensation technique is used to improve the accuracy of non-contact high-precision measuring system. To ensure the accuracy of the high-precision non-contact four-coordinate blade profile measuring system, the geometric and thermal error compensation model is proposed in this paper. The system is composed of three orthogonal coordinate axes (X, Y and Z) and a rotation axis R. The coordinate transformation matrix can be calculated by the mathematical model of rigid body which is established according to the related theoretical analysis. Three-beam interferometer and standard gauge block are adopted to verify the geometric error of the system. In the thermal deformation error compensation, wavelet neural network model is established. The thermal and geometric error compensation methods are analyzed and the experimental results are given.

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.

Improving the Accuracy of Multi-Axis Machines Through On-Line Error Compensation Using Neural Networks

1998 ◽  
Author(s):  
Abderrazak El Ouafi ◽  
Michel Guillot ◽  
Abdellah Bedrouni
Keyword(s):  
Error Compensation ◽  
Error Modeling ◽  
Precision Engineering ◽  
Dimensional Error ◽  
New Approach ◽  
Turning Center ◽  
On Line ◽  
Dynamic Errors ◽  
Compensation Approach ◽  
Compensation Function

Abstract This research is devoted to one of the most fundamental problems in precision engineering: multi-axis machines accuracy. The paper presents a new approach designed to support the implementation of software error compensation of geometric, thermal and dynamic errors for enhancing the accuracy of multi-axis machines. The accuracy of multi-axis machines can be significantly improved using an intelligent integration of sensor information to perform the compensation function. The compensation process consists of the following major steps carried out on-line: continuous monitoring of the machine conditions using position, force, speed and temperature sensors mounted on the machine structure. Error forecasting through sensor fusion. Volumetric error synthesis and software compensation. To improve the effectiveness of error modeling, an artificial neural network is extensively applied. Implemented on a turning center, the compensation approach has enabled improvement of the machine accuracy by reducing the maximum dimensional error from 70 μm initially to less than 4 μm.

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.

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