Study on soft-sensing of mill material level based on data fusion in neural network

摘要：

Aiming at the problem that the detection of the mill material level is not accurate by using conventional methods, this paper samples the parameters of the mill, include grinding sound signal, the pressure difference between import and export, and the temperature difference between import and export, combines the BP neural network, inosculates the sampling data through the multisource data fusion method, achieves the soft-sensing of the mill material level. The actual measured data in the field shows this method has good metrical performance, in support of the enough training data, the fusion result is very closed to the set-value, so this method laid the foundation for optimal control of mill.

关键词： mill material level neural network multi-source data fusion soft-sensing

作者: Ai Hong Yang Yi Wang Jian

作者单位: School of Automation Harbin University of Science and Technology,Harbin,China

会议类型: 国际会议

会议名称: The 6th International Forum on Strategic Technology(IFOST 2011)(第六届国际战略技术论坛)

会议地点: 哈尔滨

会议语种:英文

页码: 949-952

在线出版日期: 2011-08-22（万方平台首次上网日期，不代表论文的发表时间）