Reliability Assessment of Machining Accuracy on Support Vector Machine

Authors:
Chao Deng;Jun Wu;Xinyu Shao
Affiliations:
State Key Lab of Digital Manufacturing Equipment & Technology, Huazhong University of Science & Technology, Wuhan, China 430074;State Key Lab of Digital Manufacturing Equipment & Technology, Huazhong University of Science & Technology, Wuhan, China 430074;State Key Lab of Digital Manufacturing Equipment & Technology, Huazhong University of Science & Technology, Wuhan, China 430074
Venue:
ICIRA '08 Proceedings of the First International Conference on Intelligent Robotics and Applications: Part II
Year:
2008

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Abstract

In order to establish the reliability model of limited samples, a kind of support vector machine (SVM) tools LSSVM.M is used to process reliability assessment data. The choice of parameters is the key factor to affect the forecasting accuracy. To improve the accuracy, a method of advanced parameters choice is proposed, which consists of two steps. First step is to optimize the scope of parameters, gradually narrowing the initial large scope. The next step is to find out the optimal parameters. Finally, the reliability model of NC machining accuracy was established, and the prediction result in NC machining accuracy case proves that this method is valid and effective.