Volumetric Error Prediction and Compensation of NC Machine Tool Based on Least Square Support Vector Machine

2011 ◽  
Vol 4 (6) ◽  
pp. 2066-2070 ◽  
Author(s):  
Zhenya He ◽  
Xinhua Yao ◽  
Jianzhong Fu ◽  
Zichen Chen
2009 ◽  
Vol 16-19 ◽  
pp. 410-414 ◽  
Author(s):  
Chang Long Zhao ◽  
Yi Qiang Wang ◽  
Xue Song Guan

In this paper, a hybrid method of correlation analysis based on the gray theory and the least squares support vector machine is proposed to model the thermal error of spindle of NC machine tool and predict the thermal error. The gray correlation analysis is used to optimize the measuring points of spindle. The optimum measuring points and the measured thermal error of spindle are regarded as the data to be trained to build the thermal error prediction model based on the least squares support vector machine (LS-SVM). The results show that the thermal error prediction model based on LS-SVM of NC machine tool has advantages of high precision and good generalization performance. The prediction model can be used in real-time compensation of NC machine tool and can prove the process precision and reduce cost.


2012 ◽  
Vol 472-475 ◽  
pp. 2371-2376 ◽  
Author(s):  
Jin Dong Wang ◽  
Jun Jie Guo ◽  
Yu Fen Deng ◽  
Hai Tao Li

Error compensation is an effective method to improve the machining accuracy of NC machine tool. A laser tracker is used to rapidly and accurately detect the geometric error of NC machine tool in the paper. The machine tool is controlled to move on the preset path in the space, and a laser tracker is used to measure the motion trajectory of the machine tool. Each geometric error can be identified by error separation. Based on the error model of 3-axis machine tool, error compensation can be carried out by modifying the machining process (G code). Results of experiment show that, this measurement method is feasible, and modifying the G code for error compensation is also effective.


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