| PU Chun-bao,SONG Sheng-li.Hard Anodic Oxidation Process Optimization of Artificial Neural Network-based Aluminum-Copper Alloy[J],46(3):184-188 |
| Hard Anodic Oxidation Process Optimization of Artificial Neural Network-based Aluminum-Copper Alloy |
| Received:October 22, 2016 Revised:March 20, 2017 |
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| DOI：10.16490/j.cnki.issn.1001-3660.2017.03.028 |
| KeyWord:aluminum-copper alloy hard anodizing orthogonal test artificial neural network film thickness film hardness |
| Author | Institution |
| PU Chun-bao |
Engineering Institute of the Engineer Corps, PLA University of Science and Technology, Nanjing , China |
| SONG Sheng-li |
Engineering Institute of the Engineer Corps, PLA University of Science and Technology, Nanjing , China |
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| Abstract: |
| The work aims to explore the optimal process of Al-5%Cu alloy. Hard anodizing tester was used to perform hard anodizing treatment to Al-5%Cu alloy. The microstructure, film thickness and hardness of hard anodic oxide film were studied by virtue of SEM and microhardness tester. Orthogonal test and the method of artificial neural network were adopted in combination to design the experimental scheme of three-factors and three-levels. The effects of oxidation solution temperature, current density and oxidation time on hardness and thickness of hard anodizing film were studied. Process parameters of Al-5%Cu alloy anodizing were optimized by means of artificial neural network system. The hard anodizing technology could increase the surface hardness of the Al-5%Cu alloy. There acquired oxide film featured in uniform thickness, favorable surface quality and high hardness. The temperature of sulfuric acid solution was the main factor influencing microstructure and hardness of surface oxidation film. Optimum conditions of Al-5%Cu alloy hard anodizing are: the oxidation solution temperature of 9~7 ℃, current density of 4~4.8 A/dm2 and oxidation time of 115~120 min. |
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