本文關鍵詞： 游離氧化鈣軟測量 BP神經網絡 ADO MATLAB Script LabVIEW DSC　出處：《昆明理工大學》2015年碩士論文　論文類型：學位論文

【摘要】：新型干法水泥生產是我國乃至世界水泥生產的主要技術之一,其生產過程復雜、連續(xù)性強、相互影響、相互制約,尤其在窯內煅燒工序中必須保證水泥熟料游離氧化鈣(f-CaO)含量維持在合理的范圍內。隨著游離氧化鈣含量增加,熟料的強度和安定性都會大幅下降；而游離氧化鈣含量一旦低至0.5%以下時,熟料甚至會進入死燒狀態(tài)。因此,熟料游離氧化鈣含量控制的好壞直接關系到水泥產品的質量。在實際生產中,影響游離氧化鈣含量的因素較多,包括投料量,頭煤量,尾煤量,三率值等,目前主要依靠人工每小時化驗一次得到熟料f-CaO含量。而要保證水泥熟料的質量,熟料f-CaO的含量應維持在工藝需求的0.5%～2.0%之間。針對f-CaO含量難以在線測量,本論文首先利用軟測量技術中的BP神經網絡建模方法,建立了f-CaO含量軟測量模型并驗證了模型的有效性和準確性并進行了游離氧化鈣含量軟測量模型的短期校正研究；其次,為了便于對水泥熟料性能進行分析與監(jiān)控,本論文以LabVIEW作為開發(fā)平臺,開發(fā)了基于SQL2008R2的新型干法水泥生產過程數據庫的友好人機監(jiān)控界面。本論文的核心工作是利用MATLAB Script節(jié)點實現了MATLAB游離氧化鈣含量的BP神經網絡軟預測；利用LabVIEW DSC模塊設計了監(jiān)控畫面并采用均值—標準差控制圖來實現新型干法水泥熟料游離氧化鈣質量統(tǒng)計分析與預警,以指導操作人員判斷生產過程中熟料f-CaO含量是否達標,進而采取有效的控制手段；利用ADO技術實現了對數據庫的訪問與數據存儲,可方便地查詢、顯示f-CaO含量的軟預測值及其變化趨勢。本論文的特點是充分利用了LabVIEW模塊化、圖形化、每個子程序獨立調用的編程特點,以菜單方式實現了基于MATLAB Script節(jié)點、LabVIEW DSC統(tǒng)計分析模塊及ADO數據庫訪問技術的新型干法水泥生產水泥游離氧化鈣含量的軟預測與質量監(jiān)控,完成了多個系統(tǒng)功能的集成開發(fā)。本論文的工作可為新型干法水泥生產過程熟料游離氧化鈣含量的在線監(jiān)測提供一種有效途徑并奠定了一定的理論基礎。
[Abstract]:The new dry process cement production is one of the main technologies of cement production in our country and even in the world. Its production process is complex, continuous, mutual influence and mutual restriction. Especially in the kiln calcination process, the content of free calcium oxide (f-CaO) in cement clinker must be kept within a reasonable range. With the increase of free calcium oxide content, the strength and stability of clinker will decrease greatly. However, once the content of free calcium oxide is below 0.5%, the clinker will even enter into a dead state. Therefore, the quality of cement products is directly related to the control of free calcium oxide content in clinker. There are many factors that influence the content of free calcium oxide, including the quantity of feed, the quantity of coal, the quantity of tail coal, the value of three-rate, etc. At present, the f-CaO content of clinker is obtained mainly by manual test once an hour, and the quality of cement clinker should be guaranteed. The content of f-CaO in clinker should be kept between 0.5% and 2.0% of the technological requirement. The f-CaO soft sensor model is established, and the validity and accuracy of the model are verified, and the short-term correction research of the free calcium oxide soft sensor model is carried out. Secondly, in order to facilitate the analysis and monitoring of cement clinker performance, This paper takes LabVIEW as the development platform, The friendly man-machine monitoring interface of a new dry cement production process database based on SQL2008R2 is developed. The core work of this paper is to use MATLAB Script node to realize the BP neural network soft prediction of MATLAB free calcium oxide content. Using LabVIEW DSC module, the monitoring screen is designed and the mean value standard deviation control chart is used to realize the statistical analysis and early warning of the free calcium oxide quality of the new dry cement clinker, so as to guide the operators to judge whether the f-CaO content of clinker is up to standard in the production process. Then the effective control means are adopted, the database access and data storage are realized by using ADO technology, and the soft prediction value of f-CaO content and its changing trend can be easily queried. The characteristic of this paper is that the modularization of LabVIEW is fully utilized. Graphical, the programming characteristic of each subroutine calling independently, Based on MATLAB Script node LabVIEW DSC statistical analysis module and ADO database access technology, the soft prediction and quality control of free calcium oxide content in new dry cement production are realized by menu method. The work of this paper can provide an effective way for on-line monitoring of free calcium oxide content of clinker in the process of new dry cement production and lay a certain theoretical foundation.
【學位授予單位】：昆明理工大學
【學位級別】：碩士
【學位授予年份】：2015
【分類號】：TQ172.16;TP311.52

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本文編號：1529514