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Performances Prediction of Alumina Ceramics Layer by Micro Arc Oxidation Based on Artificial Neural Network

Zongwei Niu, Xiuting Wei, Zhiyong Li, Li Li, Dongshan Zhao


Alumina ceramics layer which has excellent performances can be obtained on the surface of aluminum by micro arc oxidation technique. The parameters of power supply during the process of micro arc oxidation have great influence on the thickness and quality of oxide ceramics layer. A Back Propagation artificial neural network model was established to predict the thickness and performances of the alumina layer according to the parameters of power supply. The model was trained and verified using orthogonal experiment data. The prediction results show that the model can predict the thickness and the performances of the alumina layer precisely and optimize the parameters for micro-arc oxidation of aluminum.


micro arc oxidation, artificial neural network, parameters of power supply, prediction precision.

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