Paper Title:
Optimization of Processing Parameters for Micro Arc Oxidation Based on Orthogonal Design and Support Vector Machine Regression Analysis
  Abstract

During processing, the interaction among the multi-parameters which influences the coating surface roughness is very complex. In order to gain rapidly the best parameters, this paper raises the method to optimize parameters of the micro arc oxidation based on the orthogonal design and the support vector machine regression analysis. The experiments were performed for the coating surface roughness according to the parameters designed by orthogonal on LD10. And then, the support vector machines regression was used to obtain the model between the surface roughness and the parameters according to these data. Further, the model optimized the parameters and predicted the corresponding coating with Ra1.025μm. At last, the model was verified by the experiments of single factor method under the same condition as the orthogonal experiments. The results, comparative analysis of the surface roughness of predicting and actual values generated by the same parameters, shows that the square error and the ratio of the average error influenced by the parameters expect for the temperature is less than 0.1 and 10% respectively, and the actual coating with Ra1.199μm was obtained that the parameters optimized by the model treated.

  Info
Periodical
Advanced Materials Research (Volumes 156-157)
Edited by
Jingtao Han, Zhengyi Jiang and Sihai Jiao
Pages
307-310
DOI
10.4028/www.scientific.net/AMR.156-157.307
Citation
M. Q. Pan, "Optimization of Processing Parameters for Micro Arc Oxidation Based on Orthogonal Design and Support Vector Machine Regression Analysis", Advanced Materials Research, Vols. 156-157, pp. 307-310, 2011
Online since
October 2010
Authors
Export
Price
$32.00
Share

In order to see related information, you need to Login.

In order to see related information, you need to Login.

Authors: Seung Hwan Oh, Jung Ho Kang, Won Sik Joo, Xue Guan Song, Hyeung Geol Kong, Young Chul Park
Abstract:The optimization of gate valve was performed using Kriging based approximation model. The DACE modeling, known as the one of Kriging...
901
Authors: Xue Hui Wang, Ming Jun Feng, Can Zhao
Abstract:The mechanical properties of flat end mill is analyzed the high-speed milling, the linear model for milling force is established. And the...
254
Authors: Yong He Deng
Chapter 2: Building Technology Science
Abstract:.It is availability to improve GM(1,1) forecasting precision based on the combination of GM(1,1) model and linear regression.But,it is no...
229
  | Authors: Jia Li Yang, Wei Min Wang, Yong Jiang Zhu, Ya Zhang
Chapter 7: Condition Monitoring and Fault Diagnosis
Abstract:This paper focus on rotor-bearing system parameter identification with impulse excitation in horizon and vertical which is based on Backward...
683
Authors: Xiao Yan Gong, Jun Guo, Dong Hui Yan, Zhe Wu, He Xue
Chapter 16: Mining Engineering and Coal Mining
Abstract:In order to predict accurately gas concentration in driving ventilation process under different gas emission and different ventilation scheme...
2997