个人信息Personal Information
教授
博士生导师
硕士生导师
性别:男
毕业院校:大连理工大学
学位:博士
所在单位:控制科学与工程学院
学科:控制理论与控制工程
办公地点:创新园大厦A614
联系方式:刘全利 大连理工大学控制科学与工程学院 邮编:116024 电话:0411-84705516
电子邮箱:liuql@dlut.edu.cn
Granular Computing Concept based long-term prediction of Gas Tank Levels in Steel Industry
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论文类型:会议论文
发表时间:2014-08-24
收录刊物:EI、CPCI-S、CPCI-SSH
卷号:47
期号:3
页面范围:6105-6110
关键字:Steel industry; LDG system; prediction; regression model; Granular Computing
摘要:The converter gas, especially Linz Donawitz converter gas (LDG), is one of the most significant secondary energy resources in a large scale steel plant. For such a thing, the accurate prediction for the gas tank levels largely contributes to the energy optimization operations. Taking the LDG system of a steel plant in China into consideration, a regression model based on the Granular Computing (GrC) is proposed in this study to provide a long-term prediction for the LDG tank levels, in which the data segments are entirely considered for the prediction horizon extension rather than the generic data point-oriented modeling. For being more practical, this study specially granulates the initial data with regard to industrial semantic meaning. And, different from ordinary time series analysis, this method considers the factor related to the gas tank levels. Bearing this in mind, the fuzzy rules by adopting a fuzzy C-means based clustering is established. To verify the effectiveness of the proposed method, a series of practical experiments by using the industrial data coming from the energy data center of this plant are conducted, and the results demonstrate the practicability of the proposed approach.