Literature DB >> 28336187

The chaotic characteristic of the carbon-monoxide utilization ratio in the blast furnace.

Dengfeng Xiao1, Jianqi An2, Yong He3, Min Wu3.   

Abstract

In this paper, carbon monoxide utilization ratio (CMUR) is served as a real-time index to evaluate the energy consumption of blast furnace (BF), and the chaotic analysis method is also presented to study the characteristic of CMUR. Firstly, the time series data measured from two representative BFs are adopted as the sample to investigate the characteristics of CMUR. Secondly, the phase space model of CMUR is reconstructed, and two key related parameters of the model are derived as well. Finally, the value of the chaotic attractor's saturated correlative dimensions in the reconstructed phase space of CMUR is obtained. The result shows that the sample time series of these two BFs have chaos property. Furthermore, the development process of CMUR is also proved to be the chaotic process. It provides a solid foundation for us to further study the chaotic predication and control of CMUR, which helps us to better master the variational tendency of CMUR and provides the effective operation guidance for the BF on the spot to reduce the energy consumption in BF.
Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Blast furnace (BF); Carbon monoxide utilization ratio (CMUR); Iron-making; Phase space reconstructed; Saturated correlative dimension

Year:  2017        PMID: 28336187     DOI: 10.1016/j.isatra.2017.03.004

Source DB:  PubMed          Journal:  ISA Trans        ISSN: 0019-0578            Impact factor:   5.468


  1 in total

1.  A Novel Online Sequential Extreme Learning Machine for Gas Utilization Ratio Prediction in Blast Furnaces.

Authors:  Yanjiao Li; Sen Zhang; Yixin Yin; Wendong Xiao; Jie Zhang
Journal:  Sensors (Basel)       Date:  2017-08-10       Impact factor: 3.576

  1 in total

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