Molten Steel Breakout Prediction Based on Genetic Algorithm and BP Neural Network in Continuous Casting Process

摘要：

In this paper, a compound sticking breakout prediction model including two kinds of modules, the time-sequence module of single thermocouple and the space module of multi-thermocouple was presented. The GA-BP neural network method with the genetic algorithm optimizing the original weights and thresholds of BP neural network, was used for building time-sequence module. Compared with traditional BP neural network, GA-BP neural network could avoid the defects that the results of traditional BP neural network are easily fall into local minimum point, and identify temperature patterns of sticking breakout more accurately. The testing results show the quote rate and accuracy rate for sticking breakout prediction have both achieved 100％.

关键词： Continuous casting Breakout prediction BP neural network Genetic algorithm

作者: JI Cheng CAI Zhao-zhen TAO Nai-biao YANG Ji-lin ZHU Miao-yong

作者单位: School of Materials and Metallurgy, Northeastern University, Shenyang 110819, Liaoning, China

会议类型: 国际会议

会议名称: The 31st Chinese Control Conference(第三十一届中国控制会议)

会议地点: 合肥

会议语种:英文

页码: 3402-3406

在线出版日期: 2012-07-01（万方平台首次上网日期，不代表论文的发表时间）