WANG Ping
,
HUANG Zhenyi
,
ZHANG Mingya
,
ZHAO Xuewu
钢铁研究学报(英文版)
Mechanical property prediction of hot rolled strip is one of the hotspots in material processing research. To avoid the local infinitesimal defect and slow constringency in pure BP algorithm, a kind of global optimization algorithm—particle swarm optimization (PSO) is adopted. The algorithm is combined with the BP rapid training algorithm, and then, a kind of new neural network (NN) called PSOBP NN is established. With the advantages of global optimization ability and the rapid constringency of the BP rapid training algorithm, the new algorithm fully shows the ability of nonlinear approach of multilayer feedforward network, improves the performance of NN, and provides a favorable basis for further online application of a comprehensive model.
关键词:
particle swarm optimization algorithm;BP neural network;hot continuous rolling strip;mechanical
HOU Qingyu
,
HUANG Zhenyi
,
WANG Jingtao
钢铁研究学报(英文版)
The effect of austempering temperature on the microstructure and properties of a high chromium white cast iron was investigated with the Rietveld refinement method. The result shows that the upper bainite exists in the sample austempered at 623 K and the martensite, lower bainite, M7C3, and retained austenite exist in the samples austempered at 563 K and 593 K. The relative content of the retained austenite increases with increasing the austempering temperature from 563 K to 623 K. The higher hardness, impact toughness and impact abrasive wear resistance can be obtained for the specimen austempered at 593 K.
关键词:
high chromium white cast iron;austempering;retained austenite;Rietveld refinement;microstructure;properties
