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The Static Model of Oxygen Converter Devanadium
Author: YangQi
Tutor: CaoChangXiu
School: Chongqing University
Course: Control Engineering
Keywords: Converter vanadium Radial basis function neural network Genetic Algorithms Static model
CLC: TP399
Type: Master's thesis
Year: 2002
Downloads: 167
Quote: 3
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Abstract
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Vanadium is a very important metal , widely used in metallurgy, non-ferrous metal processing , chemical , electronics and aerospace . China has abundant vanadium-titanium magnet resources , is one of the world's four major vanadium producing countries . Converter vanadium is the main mode of production . Converter vanadium is a multi- multi-phase high-temperature chemical reaction process , the reaction mechanism is very complex , many factors , raw materials, process of environmental change is not easy manual control . The production process for to increase vanadium extraction technical level , changing the the index fluctuations shortcomings in the production process , computer control , in order to reduce the effect of the the vanadium extraction operation in human factors . Papers from the point of view of engineering applications , for of our converter mention the status of the vanadium manual operation in the development process of vanadium extraction static model , converter vanadium extraction for a particular study , considering the poor adaptability of the traditional mathematical model , it is difficult to transplant the shortcomings , RBF neural networks and genetic algorithms , artificial intelligence technology to develop a static model with good self - learning and adaptive capacity . The paper introduces the significance of the establishment of vanadium extraction static model , discussed the research and application situation and development trends of the converter model at home and abroad , in-depth analysis of the advantages and disadvantages of the various modeling methods . The complexity of the process for extracting vanadium proposed converter vanadium modeling neural network as the main techniques , in combination with other artificial intelligence techniques to establish a more accurate model than the traditional mathematical model . The paper combines the characteristics of the process principles and practice of Vanadium identify Vanadium Internal factors influencing the main factors affecting the static model . And application of RBF neural network to establish the oxygen blowing time sub-model , sub-model of coolant , and completion of the RBF neural network the number of neurons , Spread and other parameters optimization combined with genetic algorithm , the model has a strong generalization ability . Simulation results show that the algorithm has faster convergence rate and strong ability to learn . Finally , we use object-oriented visual Visual C the 6 .0 programming language , developed vanadium extraction Static Model software .
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