Chaotic prediction of carbon-monoxide utilization ratio in the blast furnace
| Autor: | Min Wu, Jianqi An, Yong He, Dengfeng Xiao |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
0209 industrial biotechnology
Engineering Blast furnace Series (mathematics) business.industry Chaotic 02 engineering and technology Energy consumption Sample (graphics) 020901 industrial engineering & automation Dimension (vector space) Phase space 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Radial basis function Artificial intelligence business Algorithm |
| Zdroj: | 2016 35th Chinese Control Conference (CCC). |
| DOI: | 10.1109/chicc.2016.7554864 |
| Popis: | The carbon-monoxide utilization ratio (CMUR) is a significant factor for the energy consumption in the blast furnace (BF). CMUR cannot be well controlled on the spot due to the low predication in the previous research. In this paper, a chaotic prediction method is presented to forecast the variation tendency of CMUR. Firstly, CMUR time series sample data are acquired from two representative BFs as the sample. Then, the phase space reconstruction technology is employed to reconstruct the phase space of CMUR. Finally, based on the obtained value of the embedded dimension m and the lag-time τ in the CMUR's reconstructed phase space, the CMUR can be predicted by using chaos radial basis function (RBF) prediction method. The result shows the chaotic prediction model has high precision rate, which builds the foundation and guidance for the control of CMUR, so as the spot operation of BF. |
| Databáze: | OpenAIRE |
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