Artificial neutral network prediction of the microstucture of 60Si2MnA rod on its controlled rolling and cooling process parameters

被引：10

作者：

Jiahe, Ai ^{[1
]}

Jiang, Xu ^{[1
]}

Huiju, G.Gao ^{[1
]}

Yaohe, Hu ^{[1
]}

Xishan, Xie ^{[1
]}

机构：

[1] School of Materials Science and Engineering, University of Science and Technology

来源：

Materials Science and Engineering: A | 2003年 / 344卷 / 1-2期

关键词：

60Si2MnA steel; Artificial neural network; Controlled rolling and cooling process parameters; Microstructures;

D O I：

10.1016/S0921-5093(02)00444-6

中图分类号：

学科分类号：

摘要：

An artificial neural network (ANN) model was developed for prediction of the microstructure of the 60Si2MnA spring steel rod based on its controlled rolling and cooling process parameters. The ANN predicted results show that the interlamellar pearlite spacing, the ferrite content and the average ferrite grain size all decreases rapidly with the increase of the cooling rate from the rod layer to the coil collecting station, and the effect of the rod-laying temperature and the finishing temperature on the microstructure is not obvious. The ANN model can predict the microstructure whether the process parameters interact or not, so it is critical for the quality control of the 60Si2MnA rod and will be widely used in its controlled rolling and cooling process. © 2002 Elsevier Science B.V. All rights reserved.

引用

页码：318 / 322

页数：4

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