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

机译:基于正交设计和支持向量机回归分析的微电弧氧化处理参数的优化

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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.
机译:在加工过程中,影响涂层表面粗糙度的多参数之间的相互作用非常复杂。为了迅速获得最佳参数,本文提高了基于正交设计和支持向量机回归分析优化微电弧氧化参数的方法。根据通过在LD10上的正交设计的参数进行涂层表面粗糙度进行实验。然后,使用支持向量机回归来获得根据这些数据的表面粗糙度和参数之间的模型。此外,该模型优化了参数,并用RA1.025μm预测相应的涂层。最后,通过与正交实验相同的条件下单因素方法的实验验证了该模型。结果,对相同参数产生的预测和实际值的表面粗糙度的比较分析表明,平方误差和受限影响的平均误差的比例分别小于0.1和10%,而且获得了RA1.199μm的实际涂层,使得经型号优化的参数。

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