Thermal Error Measurement, Modeling and Compensation for Motorized Spindle and the Research on Compensation Effect Validation

2014 ◽  
Vol 889-890 ◽  
pp. 1003-1008 ◽  
Author(s):  
Yu Qing Fu ◽  
Wei Guo Gao ◽  
Jin Yu Yang ◽  
Qing Zhang ◽  
Da Wei Zhang
Keyword(s):  
Compensation Effect ◽  
Great Influence ◽  
Thermal Characteristics ◽  
Thermal Error ◽  
Shift Function ◽  
Linear Regression Method ◽  
Motorized Spindle ◽  
Verification Method ◽  
Machining Center ◽  
Thermal Error Model

The motorized spindle is a primate part of the machine tool and its thermal characteristics have great influence on the accuracy of the machine tools. The thermal errors of the spindle of a certain type of precision horizontal machining center were measured with PLC acquisition system. By multivariate linear regression method, the axial thermal error model was built. Online real-time error compensation was implemented by applying the FANUC 18i CNC system external machine coordinate system shift function. A verification method was proposed which include three steps: model validation, compensation validation and experimental machining verification. The accuracy of the model was 84.1%, 64.9% and 49.4% respectively. The quantitative analysis results showed the precision was effectively improved and the compensation method was reliable.

scholarly journals Thermal Characteristics Analysis for Motorized Spindle System of CNC Machining Center

2019 ◽  
Vol 257 ◽  
pp. 02003
Author(s):  
Xiaolei Deng ◽  
Xinghui Zhang ◽  
Mucheng Zhang ◽  
Yibo Zhou ◽  
Huan Lin ◽  
...  
Keyword(s):  
Thermal Characteristics ◽  
Thermal Error ◽  
Cnc Machining ◽  
Transfer Coefficients ◽  
Motorized Spindle ◽  
Element Analysis ◽  
Spindle System ◽  
Heat Transfer Coefficients ◽  
Machining Center ◽  
Characteristics Analysis

Based on the comprehensive analysis of the heat sources of the motorized spindle system, the thermal loads, including the heat generation of bearing friction and the electromagnetic loss of the built-in motor, are carried out for a machining center motorized spindle system. And then, the convective heat transfer coefficients of the whole spindle system are analyzed. The thermal characteristics of the motorized spindle system are calculated by finite element analysis. The steady state temperature field distribution of the motorized spindle is obtained. It provides some references for improving the thermal characteristics of the motorized spindle and reducing the difficulty of thermal error compensation.

The Precision Horizontal Machining Center Integrated Dynamic Accuracy Modeling Based on Multi-Body System Theory

2013 ◽  
Vol 364 ◽  
pp. 87-91
Author(s):  
Li Gang Cai ◽  
Chuan Ming Xiao ◽  
Qiang Cheng ◽  
Zhi Feng Liu ◽  
Pei Hua Gu
Keyword(s):  
Thermal Error ◽  
Linear Regression Method ◽  
Characteristic Matrix ◽  
Geometric Accuracy ◽  
Dynamic Accuracy ◽  
Machining Center ◽  
Line Measurement ◽  
Relation Model ◽  
Multi Body ◽  
Thermal Error Model

According to multi-body theory, establish the precision horizontal machining centers characteristic matrix and geometric accuracy model, and then establish the relation model between thermal error and collected temperature according to the five line measurement method and multiple linear regression method, which will be studied next. After the superposition of geometric accuracy model and thermal error model, getting precision horizontal machining center integrated dynamic accuracy model.

Thermal Error Modeling and Compensating of Motorized Spindle Based on Improved Neural Network

2010 ◽  
Vol 129-131 ◽  
pp. 556-560 ◽  
Author(s):  
Chun Li Lei ◽  
Zhi Yuan Rui
Keyword(s):  
Neural Network ◽  
High Speed ◽  
Thermal Deformation ◽  
Influence Factors ◽  
Thermal Error ◽  
Error Modeling ◽  
Motorized Spindle ◽  
Key Factor ◽  
Manufacturing Accuracy ◽  
Thermal Error Model

In a lot of factors, thermal deformation of motorized high-speed spindle is a key factor affecting the manufacturing accuracy of machine tool. In order to reduce the thermal errors, the reasons and influence factors are analyzed. A thermal error model, that considers the effect of thermodynamics and speed on the thermal deformation, is proposed by using genetic algorithm-based radial basis function neural network. The improved neural network has been trained and tested, then a thermal error compensation system based on this model is established to compensate thermal deformation. The experiment results show that there is a 79% decrease in motorized spindle errors and this model has high accuracy.

scholarly journals Research on Thermal Error Modeling of Motorized Spindle Based on BP Neural Network Optimized by Beetle Antennae Search Algorithm

Machines ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 286
Author(s):  
Zhaolong Li ◽  
Bo Zhu ◽  
Ye Dai ◽  
Wenming Zhu ◽  
Qinghai Wang ◽  
...  
Keyword(s):  
Neural Network ◽  
Prediction Model ◽  
Bp Neural Network ◽  
High Speed ◽  
Search Algorithm ◽  
Thermal Error ◽  
Error Prediction ◽  
Machining Accuracy ◽  
Motorized Spindle ◽  
Thermal Error Model

High-speed motorized spindle heating will produce thermal error, which is an important factor affecting the machining accuracy of machine tools. The thermal error model of high-speed motorized spindles can compensate for thermal error and improve machining accuracy effectively. In order to confirm the high precision thermal error model, Beetle antennae search algorithm (BAS) is proposed to optimize the thermal error prediction model of motorized spindle based on BP neural network. Through the thermal characteristic experiment, the A02 motorized spindle is used as the research object to obtain the temperature and axial thermal drift data of the motorized spindle at different speeds. Using fuzzy clustering and grey relational analysis to screen temperature-sensitive points. Beetle antennae search algorithm (BAS) is used to optimize the weights and thresholds of the BP neural network. Finally, the BAS-BP thermal error prediction model is established. Compared with BP and GA-BP models, the results show that BAS-BP has higher prediction accuracy than BP and GA-BP models at different speeds. Therefore, the BAS-BP model is suitable for prediction and compensation of spindle thermal error.

Novel thermal error modeling method for machining centers

2014 ◽  
Vol 229 (8) ◽  
pp. 1500-1508 ◽  
Author(s):  
Xiaolong Zhu ◽  
Sitong Xiang ◽  
Jianguo Yang
Keyword(s):  
Neural Network ◽  
Vector Quantization ◽  
Thermal Deformation ◽  
Clustering Algorithm ◽  
Thermal Error ◽  
Network Clustering ◽  
Elman Neural Network ◽  
Machining Center ◽  
Adaptive Vector Quantization ◽  
Thermal Error Model

Thermal deformation is one of the main contributors to machining errors in machine tools. In this paper, a novel approach to build an effective thermal error model for a machining center is proposed. Adaptive vector quantization network clustering algorithm is conducted to identify the temperature variables, and then one temperature variable is selected from each cluster to represent the same cluster. Furthermore, a non-linear model based on output-hidden feedback Elman neural network is adopted to establish the relationship between thermal error and temperature variables. The output-hidden feedback Elman network is adopted to predict the thermal deformation of the machining center. Back propagation (BP) neural network is introduced for comparison. A verification experiment on the machining center is carried out to validate the efficiency of the newly proposed method. Experimental verification shows that the adaptive vector quantization network clustering algorithm and output-hidden feedback Elman neural network is an accurate and effective method.

Thermal Characteristic Analysis on a High Precision Turning Center’s Headstock

2013 ◽  
Vol 655-657 ◽  
pp. 305-309
Author(s):  
Yao Man Zhang ◽  
Ren Jun Gu ◽  
Jia Liang Han
Keyword(s):  
High Precision ◽  
Error Compensation ◽  
Thermal Characteristic ◽  
Thermal Characteristics ◽  
Thermal Error ◽  
Linear Regression Method ◽  
Characteristic Analysis ◽  
Precision Turning ◽  
Turning Center ◽  
Thermal Error Compensation

The performances of the high precision turning center will be influenced by the thermal characteristics of the headstock seriously, and accurately predict thermal characteristics of the headstock are helpful to improve the design level. The headstock of a high precision turning center produced by some plant has been regarded as the research objects of the paper. First the steady temperature distribution and thermal deformation of the headstock were calculated based the finite element analysis models of the headstock. Then the temperature sensitive points of the headstock were obtained by using the grey incidence analysis method. Finally the thermal error compensation model was built by using multiple linear regression method. The study lays a foundation for the thermal error compensation of the headstock of the turning center.

Optimization of Measuring Points Based on the Grey System Theory for Spindle of Machining Center

2013 ◽  
Vol 433-435 ◽  
pp. 852-855 ◽  
Author(s):  
Chang Long Zhao ◽  
Xue Song Guan
Keyword(s):  
Thermal Error ◽  
Grey System Theory ◽  
Analysis Method ◽  
Grey System ◽  
Machining Center ◽  
Key Points ◽  
Grey Correlation Analysis ◽  
Correlation Analysis Method ◽  
Measurement Experiment ◽  
Thermal Error Model

To improve processing precision of numerical machine tool ,research on analyze the thermal error of spindle, the grey correlation analysis method is used to optimize the thermal key points to build the model of temperature field on the basis of temperature measurement experiment. By optimizing, the number of temperature measuring points from 8 to 3. In this way, the precision of thermal error model and thermal error prediction can be improved.

Research on Thermal Error Compensation Technique of the Screw

2012 ◽  
Vol 482-484 ◽  
pp. 309-313
Author(s):  
Hong Xin Yue ◽  
Yan Shi ◽  
Yan Mei Xi
Keyword(s):  
Thermal Deformation ◽  
Thermal Error ◽  
Ball Screw ◽  
Cooling Fluid ◽  
Rbf Network ◽  
Machining Center ◽  
Surrounding Environment ◽  
Compensation Technique ◽  
Thermal Error Model ◽  
Thermal Error Compensation

In the system of the machine tool, the position error is directly affected by the thermal deformation of ball screw. Screw system is a complex thermal system, which is affected by the processing conditions, the processing cycle, the use of cooling fluid, and the surrounding environment. Due to non-linear and interaction of the thermal error, a RBF network thermal error model is proposed in the paper and the model is tested in XHFA2420 large machining 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.

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