通钢七号高炉专家系统的开发与应用
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摘要
为了进一步提升通钢高炉炼铁技术,实现高炉生产的优质、高产、长寿、低耗,高炉生产的自动化势在必行。而高炉专家系统是实现高炉操作智能化的关键技术之一。
本文结合通钢七号高炉专家系统设计开发这一实际项目,分析了国内外高炉专家系统开发及应用现状、高炉专家系统技术的发展趋势、炼铁工艺及其操作制度、高炉专家系统开发的基本内容和关键技术；研究了高炉异常炉况专家系统知识库知识的获取方法、知识表示和存储方法,讨论了高炉异常炉况专家系统知识库的建立方法。
为专家系统的推理判断提供了充分、准确的数据,开发了一套数据采集处理系统,提出一种合理、有效的知识表示方法,该表示方法易于实现、便于管理和推理。同时,采用可视化编程语言DELPHI开发了高炉专家系统。该系统主要由数据采集系统、铁水含硅量预报系统和高炉炉况判定系统三个子系统组成,实现了对高炉生产过程的监测和高炉热状态以及各种异常炉况的预报和判断,并针对各种预报的炉况趋势给出相应的专家操作指导意见。利用炉热指数对高炉铁水含硅量和铁水温度进行预报,实现了按铁次预报功能。
在系统具体开发、设计和实现方面,通钢七号高炉专家系统是以先进的工艺模型和增强的软硬件功能为基础,采用模块化的软件处理模式,使得该系统具有极强的兼容性、容错性和自适应性。
在整个高炉专家系统设计的过程中,所有的知识和规则都是按照不同异常炉况整理、建立的,有着较强的实用性和针对性。目前,该系统己经调试完毕并在通钢七号高炉上运行。它的成功开发对提高高炉的各项生产指标,规范高炉操作有着重要意义。
In order to further enhance the technology of blast furnace steel refining at Tonghua Iron and Steel Corporation, and to achieve the goal of high quality, high production, long life and low cost, the automation of blast furnace must be enforced. Blast furnace expert system is one of the keys to carry out blast furnace intelligent manipulation.
This paper, presented in regard to Expert System for the No.7 Blast Furnace of Tonghua Iron and Steel Corporation, analyses the applying situation, the development of the expert system from coast to coast, the process of blast furnace, the operation schedule, the foundation and the core of blast furnace expert system, and then studies the knowledge acquisition, knowledge presentation as well as knowledge storage of the knowledge base, and discusses way to build up a knowledge base for blast furnace.
A data acquisition system for blast furnace expert system is developed, and provides reliable and accurate data for it. An effective knowledge presentation which is easily realized and inferred is introduced. This expert system is developed by DELPHI. The expert system is made up of three sub-systems, which contains data collecting system, forecast system of liquid iron containing silicon and deciding system of blast furnace situation. Therefore, forecasting of manufacture process supervision, heat condition and any abnormal furnace condition comes true. According to the furnace tendency, expert guidance and suggestion is(are) provided. The hearth thermal state parameter is used for predicting silicon content and temperature in blast furnace hot metal through the tapping times.
In term of the development, designing and practicing, Expert System for the No.7 Blast Furnace of Tonghua Iron and Steel Corporation is based on the advanced process models, software and hardware applications enhanced, the system adopted the soft process mode with modularization, and was possessed of compatibility, fault-tolerance and self-adaptability.
Throughout the system design process, all the knowledge and rules are in accordance with the rules and various abnormal situation sorted out by furnace, which share a strong practical and purposeful. At present, this expert system already passed tests and is running in Tong Gang No.7 blast furnace. Its'successful development is important to enhance each manufacture target and regulate blast furnace manipulation.
本文结合通钢七号高炉专家系统设计开发这一实际项目,分析了国内外高炉专家系统开发及应用现状、高炉专家系统技术的发展趋势、炼铁工艺及其操作制度、高炉专家系统开发的基本内容和关键技术；研究了高炉异常炉况专家系统知识库知识的获取方法、知识表示和存储方法,讨论了高炉异常炉况专家系统知识库的建立方法。
为专家系统的推理判断提供了充分、准确的数据,开发了一套数据采集处理系统,提出一种合理、有效的知识表示方法,该表示方法易于实现、便于管理和推理。同时,采用可视化编程语言DELPHI开发了高炉专家系统。该系统主要由数据采集系统、铁水含硅量预报系统和高炉炉况判定系统三个子系统组成,实现了对高炉生产过程的监测和高炉热状态以及各种异常炉况的预报和判断,并针对各种预报的炉况趋势给出相应的专家操作指导意见。利用炉热指数对高炉铁水含硅量和铁水温度进行预报,实现了按铁次预报功能。
在系统具体开发、设计和实现方面,通钢七号高炉专家系统是以先进的工艺模型和增强的软硬件功能为基础,采用模块化的软件处理模式,使得该系统具有极强的兼容性、容错性和自适应性。
在整个高炉专家系统设计的过程中,所有的知识和规则都是按照不同异常炉况整理、建立的,有着较强的实用性和针对性。目前,该系统己经调试完毕并在通钢七号高炉上运行。它的成功开发对提高高炉的各项生产指标,规范高炉操作有着重要意义。
In order to further enhance the technology of blast furnace steel refining at Tonghua Iron and Steel Corporation, and to achieve the goal of high quality, high production, long life and low cost, the automation of blast furnace must be enforced. Blast furnace expert system is one of the keys to carry out blast furnace intelligent manipulation.
This paper, presented in regard to Expert System for the No.7 Blast Furnace of Tonghua Iron and Steel Corporation, analyses the applying situation, the development of the expert system from coast to coast, the process of blast furnace, the operation schedule, the foundation and the core of blast furnace expert system, and then studies the knowledge acquisition, knowledge presentation as well as knowledge storage of the knowledge base, and discusses way to build up a knowledge base for blast furnace.
A data acquisition system for blast furnace expert system is developed, and provides reliable and accurate data for it. An effective knowledge presentation which is easily realized and inferred is introduced. This expert system is developed by DELPHI. The expert system is made up of three sub-systems, which contains data collecting system, forecast system of liquid iron containing silicon and deciding system of blast furnace situation. Therefore, forecasting of manufacture process supervision, heat condition and any abnormal furnace condition comes true. According to the furnace tendency, expert guidance and suggestion is(are) provided. The hearth thermal state parameter is used for predicting silicon content and temperature in blast furnace hot metal through the tapping times.
In term of the development, designing and practicing, Expert System for the No.7 Blast Furnace of Tonghua Iron and Steel Corporation is based on the advanced process models, software and hardware applications enhanced, the system adopted the soft process mode with modularization, and was possessed of compatibility, fault-tolerance and self-adaptability.
Throughout the system design process, all the knowledge and rules are in accordance with the rules and various abnormal situation sorted out by furnace, which share a strong practical and purposeful. At present, this expert system already passed tests and is running in Tong Gang No.7 blast furnace. Its'successful development is important to enhance each manufacture target and regulate blast furnace manipulation.
引文
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2.蔡自兴,徐光佑.人工智能与应用[M],北京：清华大学出版社,1995.
3.王茂华,汪保平,惠志刚.高炉操作控制专家系统评述[J],河南冶金,2006,14(1)：3-5.
4.谢俊勇,刁日升,唐炜.攀钢1号高炉专家系统的建立与运行[J],炼铁,2007,26(3)：1-5.
5.李文杰.武钢四号高炉冶炼专家系统的研制[J],武汉科技大学学报,2004,27(3)：300-302.
6.于仲洁,陈令坤,杨天钧,左海滨,国宏伟.武钢1号高炉冶炼专家系统开发的新进展[J],钢铁研究,2006,34(4)：1-5.
7.杨春生,刘京瑞,刘永久,刘芳,蒋美华,刘祥官.邯钢7号高炉数学模型专家系统的应用[J],炼铁,2007,26(3)：6-9.
8.王刚,郑少波.高炉专家系统的开发及应用[J],上海金属,2004,26(4)：34-37.
9.康波、肖命冬、卢锡友,炼铁.韶钢2500M3高炉工艺设计特点[J],炼铁,2005,24(5)：15-19.
10.成兰伯.高炉炼铁工艺及计算[M],第一版,北京：冶金工业出版社,1991：1-52.
11.陈桂英.焦炭热反应性能对高炉透气性的影响[J],能源研究与利用,2005,20(4)：41-43.
12.华建明,张龙来.鼓风动能对高炉冶炼的影响及控制[J],炼铁,2005,24(4)：5-8.
13.卢宇飞.炼铁工艺[M],冶金工业出版社,2006.
14.吴胜利,陈辉,余晓波,徐健,王筱留.高炉理论燃烧温度计算的研究[J],钢铁,2008,43(9)：16-19.
15.赵润恩.炼铁工艺设计原理[M],第一版,北京：冶金工业出版社,1993.
16.刘琦.高炉基本操作制度的选择[J],炼铁,2004,23(1)：2-8.
17.孙守建,赵树民.高炉生产中合理送风制度的选择[J],山东冶金,2005,27(6)：69-70.
18.王维兴.高风温对高炉炼铁的重要作用[J],金属世界,2004,19(6)：29-30.
19.毕学工.高炉专家系统的研究与开发(二)[J],炼铁,2000,19(3)：50-55.
20.曾燕飞,李小伟.专家系统在湘钢4#高炉的应用[J],冶金从刊,2006,164(4)：27-30.
21.施金良,贾碧,余群威,兰寿兵.人工智能高炉冶炼过程专家系统[J],重庆大学学报,2005,28(5)：63-67.
22.ZALIS K. Application of expert systems in diagnostics of high voltage insulating systems[C], International Conference Solid Dielectrics,2004,2:691-894.
23. Jain M.B, Jain A., Srinivas M.B..A web based expert system shell for fault diagnosis and control of power system equipment[C],Condition Monitoring and Diagnosis,2008,2:1310-1313.
24. Kumar B.R., Shanmugam J., Janarthanan S., Santhiseela R.. Development of expert system for the design of airborne equipment[C], Digital Avionics Systems Conference,2004,(2):6.C.4-61-10.
25. Wiriyacoonkasem S., Esterline A.C.. Adaptive learning expert systems[C], Southeastcon 2000,2000:445-448.
26. Kusiak A.. Expert systems and optimization[J], IEEE Transactions on Software Engineering,1989,15(8):1017-1020.
27. Shenassa M.H., Khakpour K.. Knowledge base expert system for tuning PID controllers using wireless technology[C], Computer and Communication Engineering,2008:310-313.
28. Jain M.B., Srinivas M.B.. Jain A.,A novel Web based Expert System Architecture for on-line and off-line fault diagnosis and control (FDC) of transformers [C], Tencon 2008,2008:1-5.
29. Yan Qu, Tao Fu, Huizhong Qiu. A Fuzzy Expert System Framework Using Object-Oriented Techniques[C] Computational Intelligence and Industrial Application, 2008,(2):474-477.
30. Klampfer S.,Globacnik G., Mohorko J., Cucej Z.. Expert systems design for automatic analysis of communication network simulation results[C], Systems, Signals and Image Processing,2008:37-40.
31. Wenjun Hou, Xiangji Li, Yue Jin, Jia Wu.A Study of Intelligent Decision-Making System Based on Neural Networks and Expert System[C], Cyberworlds,2008:811-814.
32.关启学,王健波.RETE算法的简化与实现[J],科技信息,2008,16(2)：85.
33.黄务兰.一种新的基于产生式规则的推理树结构[J],微电子学与计算机,2007,24(4)：76-78.
34.谢坤武,程业勤.基于数据库技术专家系统的设计与实现[J],湖北民族学院学报,2005,23(2)：193-196.
35.刘祥官,刘芳.高炉炼铁过程优化与智能控制系统[M],第一版,北京：冶金工业出版社,2003：116-146.
36.易栗,徐用懋,马竹梧.高炉异常炉况诊断专家系统[J],冶金自动化,2002,15(1)：15-17.
37.程素森,孙磊,杨天钧.异常炉况高炉冷却板及炉衬非稳态温度场[J],北京科技大学学报,2004,26(4)：360-364.
38.吴海刚,顾继雄,忻毅,殷侏华,马洪.上钢一厂2500 M3高炉专家系统的开发与应用[J],炼铁,2004,23(1)：31-34.
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