caa a22 4500 463230612 CHVBK 20180405153240.0 cr unu---uuuuu 170326e20070401xx s 000 0 eng 10.1007/s10853-006-1278-y doi (NATIONALLICENCE)springer-10.1007/s10853-006-1278-y Artificial neural network prediction of heat-treatment hardness and abrasive wear resistance of High-Vanadium High-Speed Steel (HVHSS) [Elektronische Daten] [Xu Liujie, Xing Jiandong, Wei Shizhong, Peng Tao, Zhang Yongzhen, Long Rui] 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. Springer Science+Business Media, LLC, 2006 Liujie Xu State Key Laboratory for Mechanical Behavior of Materials, Xi'an Jiaotong University, 710049, Xi'an, P.R. China aut Jiandong Xing State Key Laboratory for Mechanical Behavior of Materials, Xi'an Jiaotong University, 710049, Xi'an, P.R. China aut Shizhong Wei Henan Engineering Research Center for Wear of Material, 471003, Luoyang, P.R. China aut Tao Peng School of Materials Science and Engineering, Henan University of Science and Technology, 471003, Luoyang, P.R. China aut Yongzhen Zhang School of Materials Science and Engineering, Henan University of Science and Technology, 471003, Luoyang, P.R. China aut Rui Long Henan Engineering Research Center for Wear of Material, 471003, Luoyang, P.R. China aut Journal of Materials Science Kluwer Academic Publishers-Plenum Publishers; http://www.springer-ny.com 42/8(2007-04-01), 2565-2573 0022-2461 42:8<2565 2007 42 10853 https://doi.org/10.1007/s10853-006-1278-y text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s10853-006-1278-y text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Liujie Xu State Key Laboratory for Mechanical Behavior of Materials, Xi'an Jiaotong University, 710049, Xi'an, P.R. China aut NATIONALLICENCE 700 1- Jiandong Xing State Key Laboratory for Mechanical Behavior of Materials, Xi'an Jiaotong University, 710049, Xi'an, P.R. China aut NATIONALLICENCE 700 1- Shizhong Wei Henan Engineering Research Center for Wear of Material, 471003, Luoyang, P.R. China aut NATIONALLICENCE 700 1- Tao Peng School of Materials Science and Engineering, Henan University of Science and Technology, 471003, Luoyang, P.R. China aut NATIONALLICENCE 700 1- Yongzhen Zhang School of Materials Science and Engineering, Henan University of Science and Technology, 471003, Luoyang, P.R. China aut NATIONALLICENCE 700 1- Rui Long Henan Engineering Research Center for Wear of Material, 471003, Luoyang, P.R. China aut NATIONALLICENCE 773 0- Journal of Materials Science Kluwer Academic Publishers-Plenum Publishers; http://www.springer-ny.com 42/8(2007-04-01), 2565-2573 0022-2461 42:8<2565 2007 42 10853 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer