Artificial neural network prediction of heat-treatment hardness and abrasive wear resistance of High-Vanadium High-Speed Steel (HVHSS)
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The hardness and abrasive wear resistance were measured after High-Vanadium High-Speed Steel (HVHSS) were quenched at 900 °C–1100 °C, and then tempered at 250 °C–600 °C. Via one-hidden-layer and two-hidden-layer Back-Propagation (BP) neural networks, the non-linear relationships of hardness (H) and abrasive wear resistance (ε) vs. quenching temperature and tempering temperature (T1, T2) were established, respectively, on the base of the experimental data. The results show that the well-trained two-hidden-layer networks have rather smaller training errors and much better generalization performance compared with well-trained one-hidden-layer neural networks, and can precisely predict hardness and abrasive wear resistance according to quenching and tempering temperatures. The prediction values have sufficiently mined the basic domain knowledge of heat treatment process of HVHSS. Therefore, a new way of predicting hardness and wear resistance according to heat treatment technique was provided by the authors.
KeywordsAustenite Martensite Wear Resistance Abrasive Wear Heat Treatment Temperature
This work is supported by Key Scientific and Technological Breakthrough Project of Henan Province, China (No.0322020300).
- 5.Wei S, Zhu J, Xu L (2005) Trans Mater Heat Treat 26:44Google Scholar
- 6.Wei SZ, Long R (2001) Cement 8:31Google Scholar
- 9.Liu H, Liu Y, Yu S (2000) Tribol 20(6):401Google Scholar
- 13.Su J, Dong Q, Liu P, Li H, Kang B (2003) J Wuhan Univ Technol-Mat Sci Edit 18:50Google Scholar
- 15.Mackay, David JC (1992) Neural Comput 4:415Google Scholar
- 17.Liu P, Lei J, Jing X, Tian B (2005) Trans Mater Heat Treat 26:86Google Scholar
- 18.Su J, Dong Q, Liu P, Li H, Kang B (2003) Trans Nonferrous Met Soc China 13:1419Google Scholar
- 19.Guo J, Yang Z, in “Analysis and Design of Neural Network Based on Matlab6.5”(Publishing House of Electronics Industry, Beijing, 2003) pp 313Google Scholar
- 20.Wei S, Zhu J, Long R (2004) Hot Work Technol 12:31Google Scholar
- 21.Tong J, Zhang W (1994) Chinese J Mech Eng 30:103Google Scholar