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Application of Artificial Neural Network to Predicting Hardenability of Gear Steel

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Abstract

The prediction of the hardenability and chemical composition of gear steel was studied using artificial neural networks. A software was used to quantitatively forecast the hardenability by its chemical composition or the chemical composition by its hardenability. The prediction result is more precise than that obtained from the traditional method based on the simple mathematical regression model.

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References

  1. YANG Qi-ping, YANG Pei-yi, ZHANG Jie. Present Condition and Development of the Automobile Gear Steels [J]. Automobile Technology and Material, 1997, 6: 1–4 (in Chinese).

    Google Scholar 

  2. REN Yuan-he. Effects of Metallurgical Factors on Hardenabil-ity of Pinion Steel [J]. Steel Making, 1995, 6: 16–19 (in Chinese).

    Google Scholar 

  3. ZUO Xiu-rong, JIANG Mao-fa, XUE Xiang-xin. Composition Adjusting of Gear Steel in LF-VD Process Based on Property Prediction by Artificial Nerve Network [J], Steel Making, 2001, 17(4): 18–21 (in Chinese).

    Google Scholar 

  4. XIANG Cheng-yun. Structural Alloy Steel [M]. Beijing: Metallurgical Industry Press, 1999 (in Chinese).

    Google Scholar 

  5. YU Bo-hai. Calculation Performance of Automobile Gear Steel [J]. Special Steel, 1997, 18(5): 45–48 (in Chinese).

    Google Scholar 

  6. WANG Xu, WANG Hong, WANG Wen-hui. Application and Theory of Artificial Neural Networks [M]. Shenyang: Northeastern University Press, 2000 (in Chinese).

    Google Scholar 

  7. Dobrzanski L A, Sitek W. The Modeling of Hardenability Using Neural Networks [J]. Journal of Materials Processing Technology, 1999, 92-93: 8–14.

    Article  Google Scholar 

  8. Dobrzanski L A, Sitek W. Application of a Neural Network in Modeling of Hardenability of Constructional Steels [J]. Journal of Materials Processing Technology, 1998, 78: 59–66.

    Article  Google Scholar 

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Authors and Affiliations

  1. State Key Laboratory of Rolling and Automation, Northeastern University, Shenyang, Liaoning, 110004, China

    Xiu-hua Gao (Post-Doctor, Associate Professor), Ke-min Qi, Tian-yong Deng & Chun-lin Qiu

  2. Technical Center, Laiwu Iron and Steel Co Ltd, Laiwu, Shandong, 271104, China

    Ping Zhou & Xian-bin Du

Authors
  1. Xiu-hua Gao
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  2. Ke-min Qi
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  3. Tian-yong Deng
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  4. Chun-lin Qiu
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  5. Ping Zhou
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  6. Xian-bin Du
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Correspondence to Xiu-hua Gao.

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Gao, Xh., Qi, Km., Deng, Ty. et al. Application of Artificial Neural Network to Predicting Hardenability of Gear Steel. J. Iron Steel Res. Int. 13, 71–73 (2006). https://doi.org/10.1016/S1006-706X(06)60114-3

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  • DOI: https://doi.org/10.1016/S1006-706X(06)60114-3

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