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The Researches on Optimization Models of Flux Addition and Matte Addition in P-S Converter

Author: ZhangXuBin
Tutor: LiuGuoPing
School: Nanchang University
Course: Mechanical and Electronic Engineering
Keywords: P-S converter Data preprocessing Flux join optimization Copper matte join optimization Neural Network
CLC: TF811
Type: Master's thesis
Year: 2011
Downloads: 11
Quote: 0
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Abstract


MATTE is an important part of the blister copper smelting copper smelter , has a critical impact on the yield and quality of its blister copper . PS converter blowing process is not carried out in a completely closed environment , which involves chemical reactions , heat changes and delivery , material change , fluid power , etc. , which are seriously constrained the MATTE online real-time detection operation is achieved. The same time, in most of the domestic copper smelters MATTE operation is carried out with human experience . Seen in this light, the copper matte blowing all aspects of the optimization process operation not only directly improve the copper matte blowing determine the end point rate has laid a good foundation , but there are important practical significance for the rapid development of China 's rule of Copper . Understand the current state of development of the domestic and international copper smelting , the paper adopted the rule of plant research , in-depth understanding of the position and structure of the PS converter , copper matte material balance calculation , in-depth understanding of MATTE characteristics , the establishment of The copper matte join volume system with flux volume system . And based on the empirical formula mass balance calculation of the flux on the amount of flux prediction model predictions compared draw the pros and cons . MATTE data storage database -based system of data-driven model to provide and update clean data . The software development process , I use MATLAB and VC platform BP neural network , BP neural network optimization , and ultimately in the VC platform , the establishment of adaptive BP neural network model . The required data in order to better BP neural network algorithm , in this pre - processing : data standardization and gray correlation calculation . The final use of VC and database SQL association, created one of a set of data-driven prediction and data storage model .

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CLC: > Industrial Technology > Metallurgical Industry > Nonferrous metal smelting > Heavy metals smelting > Copper
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