近年來,隨著市場競爭的日益加劇和環保要求的不斷提高,迫切要求企業從有限的資源中不斷挖掘潛力,提高經濟效益,這給過程控制和過程優化提出了新的要求,從而也對過程建模提出了更高的要求。
一切工業生產的目的都是為了獲得合格的產品,質量控制成為所有控制的核心。為了實現良好的質量控制,就必須對產品質量或與之相關的重要過程變量進行嚴格控制。由于在線分析儀表不僅價格昂貴,而且分析儀表滯后大,最終將導致控制系統的性能下降,從而難以滿足生產要求。例如石油化工生產中精餾塔產品成分、塔板效率、反應器中反應物濃度、轉化率等參數。為解決這類變量的測量問題,軟測量技術得到了很大的發展。
本文對軟測量技術進行了深入的研究與探討,在此基礎上利用多元線性回歸、多元線性逐步回歸、人工神經網絡等方法來建立數學模型,并結合揚子石化丁二烯裝置優化改造項目,在Fisher-Rosemount公司的DeltaV DCS上成功實現了基于軟測量模型的先進控制系統。
本文的主要研究工作概括如下:
(1)首先對過程控制的發展和研究現狀做了論述。對現有的研究成果進行了分析和闡述,并指出了理論研究與實際應用中所存在的困難。
(2)揚子石化公司丁二烯生產裝置配套的DeltaV DCS沒有選擇與管理計算機系統的通訊接口。以Fisher-Rosemount公司的DeltaV DCS與PC LAN的數據傳輸為例,介紹了相應技術、實現方法及其應用。我們設計一套DeltaV DCS與PC機通訊方案,用于實時采集生產過程現場數據,并把DCS中的生產工藝數據存入數據庫中。
(3)針對數據庫中的數據我們采用多元線性回歸、多元線性逐步回歸、人工神經網絡等方法來建立相應的數學模型。
(4)OPC(OLE for Process Control)是微軟公司的對象鏈接和嵌入技術在過程控制方面的應用,為工業自動化軟件面向對象的開發提供一項統一的標準。OPC的目的是為工廠底層設備或控制室數據庫中大量數據源之間的通信提供一種標準的通信機制。
(5)利用DeltaV DCS這個開發平臺,進行組態和下裝模型,從而達到先進控制要求。
關鍵詞 軟測量 線性回歸 人工神經網絡 DeltaV DCS OPC (OLE for Process Control)
ABSTRACT
Recently, with the becoming severely market competition and environment requirements force companies to improve their productivity and efficiency, which poses new requirements on process control and process optimization, as a result, more severe requirements are posed on process modeling.
All industries’ purposes are getting the eligible product. The core of all controls is quantity control. In order to achieve good quantity control, we should control product quantity or correlative process variable severely. On-line analysis instruments have several disadvantages including costly price, great lag etc., which lead to descend of control system’s performance and can’t meet production requirements. For example, in order to solve these variables measure such as distillation tower production component、tray efficient、reactant concentration、conversion and so on in petrochemical produce. Soft sensor technique has greatly developed.
Soft sensor technique has been studied and discussed in this dissertation deeply. Apply multivariable linear regression、multivariable step-wise regression and artificial neural networks to establish mathematical model, and realize the advanced process control system in Fisher-Rosemount DeltaV DCS.
The research works can be summarized as follows:
(1) Discuss the development and research of process control firstly. Analyze and expatiate the existing production.
(2) Without the communication interface between DeltaV DCS and Supervise Computer, we design a scheme of communication system between DeltaV DCS and PC, and then apply it to access process data, and then deposit them to database.
(3) Make use of multivariable linear regression、multivariable step-wise regression and artificial neural networks and so on to establish corresponding mathematical model.
(4) OPC(OLE for process control),which is the application of Microsoft’s Object Linking and Embedding technology in process control system, provides a unified standard for Object-Oriented Design in industrial automation software. A standard mechanism for communicating to numerous data sources, either devices on the factory floor, or a database in a control room is the purpose for OPC.
(5) Use the flat development of DeltaV DCS to configure、download and realize the model arithmetic in DeltaV DCS to achieve advanced process control.