| ZHONG Li,LI Guo-chuan,WANG Li-wen.Multiple Ion Nitriding of Stainless Steel Optimization Design Based on BP Neural Network[J],43(2):79-82 |
| Multiple Ion Nitriding of Stainless Steel Optimization Design Based on BP Neural Network |
| Received:November 08, 2013 Revised:December 18, 2013 |
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| DOI： |
| KeyWord:multiple ion nitriding BP neural network optimization design |
| Author | Institution |
| ZHONG Li |
College of Mechatronic and Automobile Engineering, Chongqing Jiaotong University, Chongqing , China |
| LI Guo-chuan |
College of Mechatronic and Automobile Engineering, Chongqing Jiaotong University, Chongqing , China |
| WANG Li-wen |
College of Mechatronic and Automobile Engineering, Chongqing Jiaotong University, Chongqing , China |
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| Abstract: |
| Objective To improve the efficiency and quality through the neural networks optimization of multiple ion nitriding process on stainless steel. Methods The influences of cycle, ethanol, CS2 and ammonia flow on the wear resistance and corrosion resistance of austenitic stainless steel 316Ti in nitriding were analyzed. A BP neural network was established, and parameters for the stainless steel circular multiple ion nitriding process were seeked through prediction. Results The process parameters error was optimized within 依5% by using BP neural network to validate the technical parameters of the process optimization. Conclusion Different from the traditional empirical method and test method, the new method realized the optimization design of multiple ion nitriding. |
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