南钢高炉操作管理系统研究与开发
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摘要
高炉炼铁是一个连续而复杂的过程,通过实时采集到的表征高炉当前运行状态的数据,可以对高炉当前的运行状况进行判断,并对高炉未来可能出现的状态进行预测。由于客观原因,这种预测只能由高炉当班工长在高炉主控室内通过观察运行状态数据进行,在主控室以外的地方很难对高炉炉况进行全面的监测。
本文介绍了在南钢现有技术条件下开发的南钢高炉操作管理系统的组成、功能、离线、在线调试、运行和应用情况。本系统通过高炉参数的自动采集和传输使得生产管理者可以在主控室以外对高炉运行趋势进行监测,安装本系统的各终端机都可以对5座高炉近24小时的各项参数数据和趋势进行浏览。本系统实现了数据资源共享,使各科室的技术人员在办公室就能够在线进行技术分析,从而使生产过程优化分析的时效性大大提高;厂长能够实时检查、监督高炉的生产操作,对高炉生产中存在的决策优化问题能够随着炉况和条件的变化及时做出调整;各个科室之间的报表交流更加频繁,做到了真正的报表共享;实现了操作-技术-管理的“三位一体”。
与同类系统相比南钢高炉操作管理系统的优点在于:
①生产管理者能够在任何安装了本系统的终端机上直观了解每座高炉的生产状况和运行趋势。
②系统实现了数据资源共享和网络管理,各个岗位上的人员可同时在线对高炉运行状况进行分析。
③系统具有强大的报表自动生成功能,能够生成包括调度日志在内的20几种报表。
南钢高炉操作管理系统已经在南钢投入应用,目前使用状态良好。该系统的使用不但为管理者操作高炉提供了方便,而且节约了公司的人力、物力和财力,为公司的增产、节能、降耗做出了贡献,具有重要的实用价值和现实意义。
Blast furnace (BF) smelting is a continuous and complex process. By collecting real-time data attributed to operating state of BF, the operation condition can be identified and the possible state can also be forecasted. Due to objective factors, BF operators can only forecast with observing running data. So it’s difficult to proceed comprehensive monitoring outside the master-control room.
This thesis introduces the composition, function, on and off line debugging, operation and application of Nangang B.F operation management system, which bases on existing technical level. This system can browse any parameter and trend of five BF in 24 hours with the terminal equipment and help the operator forecast the trend of BF through auto collecting data and transmitting. As this system maximally implement sharing of data resource and increase aging ability of optimization analysis in the BF smelting process, so it helps technical personnel carry on on-line technical analyzing and helps the leader proceed on-line checking and monitor BF smelting and makes adjusting as the change of BF state and condition. Every branch can exchange the producing report; carry out real sharing of producing report and trinity of management, operation and technique.
Comparing to other system, the merits of the system is as follows:
①Managers can visually know smelting condition and running trend of any BF by the terminal equipment installed this system.
②The system achieves sharing of the data resource and net management, any operator can proceed the on-line analysis by it.
③The system has powerful function of tables auto creating, and bring more twenty tables including schedule log.
Nangang B.F operation management system has been put into application, and goes on well. The system not only supply the convenience for manager of BF, but also save human resource and material resource and financial resource, and make contribution to increasing output, saving energy, decreasing consumption. It had important utility value and actual meaning.
本文介绍了在南钢现有技术条件下开发的南钢高炉操作管理系统的组成、功能、离线、在线调试、运行和应用情况。本系统通过高炉参数的自动采集和传输使得生产管理者可以在主控室以外对高炉运行趋势进行监测,安装本系统的各终端机都可以对5座高炉近24小时的各项参数数据和趋势进行浏览。本系统实现了数据资源共享,使各科室的技术人员在办公室就能够在线进行技术分析,从而使生产过程优化分析的时效性大大提高;厂长能够实时检查、监督高炉的生产操作,对高炉生产中存在的决策优化问题能够随着炉况和条件的变化及时做出调整;各个科室之间的报表交流更加频繁,做到了真正的报表共享;实现了操作-技术-管理的“三位一体”。
与同类系统相比南钢高炉操作管理系统的优点在于:
①生产管理者能够在任何安装了本系统的终端机上直观了解每座高炉的生产状况和运行趋势。
②系统实现了数据资源共享和网络管理,各个岗位上的人员可同时在线对高炉运行状况进行分析。
③系统具有强大的报表自动生成功能,能够生成包括调度日志在内的20几种报表。
南钢高炉操作管理系统已经在南钢投入应用,目前使用状态良好。该系统的使用不但为管理者操作高炉提供了方便,而且节约了公司的人力、物力和财力,为公司的增产、节能、降耗做出了贡献,具有重要的实用价值和现实意义。
Blast furnace (BF) smelting is a continuous and complex process. By collecting real-time data attributed to operating state of BF, the operation condition can be identified and the possible state can also be forecasted. Due to objective factors, BF operators can only forecast with observing running data. So it’s difficult to proceed comprehensive monitoring outside the master-control room.
This thesis introduces the composition, function, on and off line debugging, operation and application of Nangang B.F operation management system, which bases on existing technical level. This system can browse any parameter and trend of five BF in 24 hours with the terminal equipment and help the operator forecast the trend of BF through auto collecting data and transmitting. As this system maximally implement sharing of data resource and increase aging ability of optimization analysis in the BF smelting process, so it helps technical personnel carry on on-line technical analyzing and helps the leader proceed on-line checking and monitor BF smelting and makes adjusting as the change of BF state and condition. Every branch can exchange the producing report; carry out real sharing of producing report and trinity of management, operation and technique.
Comparing to other system, the merits of the system is as follows:
①Managers can visually know smelting condition and running trend of any BF by the terminal equipment installed this system.
②The system achieves sharing of the data resource and net management, any operator can proceed the on-line analysis by it.
③The system has powerful function of tables auto creating, and bring more twenty tables including schedule log.
Nangang B.F operation management system has been put into application, and goes on well. The system not only supply the convenience for manager of BF, but also save human resource and material resource and financial resource, and make contribution to increasing output, saving energy, decreasing consumption. It had important utility value and actual meaning.
引文
[1] 李汉江,杨雪莲.武钢 4#高炉专家系统参数的检测及对策,武汉工程职业技术学院学报,2002,14(2): 9~12
[2] 毕学工.高炉专家系统的研究与开发㈠,炼铁,2000,19 ⑵ :50~53
[3] 毕学工.高炉专家系统的研究与开发㈡,炼铁,2000,19 ⑶ :50~55
[4] 新日本制铁.新日铁におけゐ高炉用主要モデルの绍介,计测と控制,1987
[5] 岩村忠昭.プロセスの状况の分类.计测と控制,1985
[6] Yoshio Tsunozaki, Atsuhisa Takekoshi, Kocich Hashimotoet., et al. An expert System for Blast Furnace Control at Works, Nippon Kokan Technical Report. 1987, (119)PP 1~8
[7] Akira Ichihara, Satoshi kasai, Hiromasa Yamamoto, et al. Expert GO-STOP System at Kawasaki’s MiZushima Works, Iron and Steel Engineer, 1998(5)
[8] Kawasaki Steel. GO-STOP System Applied to Blast Furnace. Ironmaking Proceeding,1997
[9] Shigonbu, Kobayshi. Knowledge Compilation and Refinement for Fault Diagnosis. IEEE Exepert,1991,(10):39~46
[10] Yasuo. Takashi S, Masaaki S, et al. Application of a self-learning function to an expert system for blast furnace heat control. ISIJ International,1990,30(2):111~117
[11] G..Brunnbauer, G.Kolb, F. Lssinger, et al. Current Status for Blast Furnace Operation by Closed- loop Expert System AT VA-STAHL, Mc Master Symposium, Hamilton/Canada, Mai, 1999
[12] M. Cross ,R. D. Gibson and J.T.Moon. Development and Validation of A Practical Theory to Describe Gas Flow Through the Blast Furnace. Seminar on Heat and Mass Transfer in Metallurgical Systems. Dubrovnik, Yugoslavia(1997)
[13] H. Zeisel. Mathem at Ische Modellierung and Numerische Simulation der Vorg nge im Hochofen. Doctor Thesis, University of Linz(1995). Published by University tsverlag Rudolf Trauner,Linz
[14] Haimi S, Inkala P, Kivijarvj. Advabces In the Application of Blast Furnace Control Models at Rautaruukkts Raahe Blast Furnace. 1992 Ironmaking Conference Proceedings. USA:1992,149~158
[15] Tetsuya Y, Toshirou S, et al. Blast Furnace operational system with the application of advanced go-stop system at mizushima a works, Proceedings of sixth international iron and steel congress.Nagoya:ISIJ,1990,364~371
[16] Hirata T, Ramamura K, Mormoto S, et al. Blast Furnace Operation System Using Neural Net Works And Knowledgebase. Proceedings of the Sixth International Iron and Steel Congress,Nagoya:ISIJ,1990,23~27
[17] Mcgraw K, Briggs K H. Knowledge Acquisition; Principles and Guidelines, New Jersey; Prentice Hall, Inc., 1998,11~13
[18] Hirsh H, Noordewier M. Using background knowledge to improve inductive learning. IEEE Expert,1994,9(5):3~6
[19] F. Lasinger, A. Klinger, M. Lehner. 奥钢联 Vairon 高炉自动化(专家系统)的应用及初步成果.钢铁,2002,37(12):9~13
[20] H. Druchenthaner, B. Sch rz M. Schaler. Vairon 高炉优化软件包——专家系统.钢铁,2000,35(8):13~17
[21] 周渝生,许祖泽.从拉赫钢铁厂看 21 世纪的高炉炼铁技术.宝钢科技,1998,2:54~59
[22] 戴术英. 高炉奥钢联林茨厂的应用. 昆钢科技,2002,1:20~23
[23] 张文新. 国内外高炉的生产现状及其发展趋向.钢铁钒钛,1997,18(2):35~43
[24] 毕学工.瑞典律勒欧厂 2 号高炉超强化冶炼的分析.炼铁,1994,13(6):28~32
[25] 毕学工.高炉过程数学模型及计算机控制,北京:冶金工业出版社,1996
[26] 毕学工.人工智能和专家系统在钢铁工业中的应用,武汉钢铁学院学报,1995,18(2):146~154
[27] 刘金琨等.高炉铁水硅含量的神经网络时间序列预报,钢铁研究学报,1996(3):63~66
[28] 刘金琨,邓守强.高炉热状态预测专家系统的设计及实现方法,东北大学学报(自然科学版),1995,16(5):473~477
[29] 刘金琨,王树青,张建明等.高炉实时控制专家系统存在的问题及其解决法,浙江大学学报(工学版),2000,34(6):613~618
[30] 陈令坤,汪勇,付连春等.高炉冶炼专家系统在炉型管理中的应用,钢铁,2000,35(9):5~9
[31] 郭宏飞,周伟.高炉异常炉况判断专家系统的设计与实现,东北大学学报(自然科学版),1995,18(2):178~182
[32] 朱敏,李兰滨.高炉热状态判断专家系统机器学习子系统的设计,钢铁研究学报,1997(增刊):7~10
[33] 陈亮.高炉炉底侵蚀状态数学模拟模型的研究:[硕士学位论文],沈阳东北大学,1997
[34] 钱亚平,卢鸣,张雷等.马钢 2500m~3 高炉网络互联及实时监控的实施,炼铁,2003(增刊):24~26
[35] 陈令坤,汪勇,付连春等.武钢 4 号高炉冶炼专家系统的应用概况,钢铁,1999(10),150~153
[36] 刘祥官,刘芳,刘元和等.等莱钢 1 号 750m~3 高炉智能控制专家系统,钢铁,2002,37(8):18~22
[37] 刘祥官,刘显著,蒋美华等.智能控制专家系统在莱钢高炉的应用,冶金自动化,2002(6):15~18
[38] 刘祥官,王义康.新临钢 380m~3 高炉专家系统的应用,炼铁,2003(2):24~26
[39] 高贤成,张国营,殷玉祥等.炼铁优化专家系统在济钢高炉上的应用,钢铁,2000,35(6):5~9
[40] 刘祥官,刘芳,李满喜等.炼铁优化专家系统在济钢高炉的应用,冶金自动化,2001(2):15~19
[41] 冯震, 董世泽 . 高炉专家系统在本钢五号高炉的应用, 本溪冶金高等专科学校学报,2003,5(4):29~31
[42] 朱子宗,邹德,沈勇玲.安钢 4 号高炉能量管理优化及预测系统研究,冶金能源,1998,17(6):3~5
[43] 安云沛,车玉满,刘方等.鞍钢 4 号高炉热状态专家系统的开发与应用,鞍钢技术,1997(8):6~11
[44] 王红章,袁万能,刘祥官.八钢 2#高炉专家系统的设计,新疆钢铁,1999(4):12~16
[45] 贾碧 , 施金良 , 余群威等 . 重钢 5 号高炉 综 合 诊 断专 家 系 统 的开 发与 应用 , 炼铁,2003,22(6):31~33
[46] 吴海刚,顾继雄,忻毅等.上钢一厂 2500m~3 炉专家系统的开发与应用,炼铁,2004,23(1):31~34
[47] 刘金琨,吴士杰,刘汉武等.高炉专家系统技术展望,钢铁研究学报,1997,9(3):59~62
[48] 成兰伯.高炉炼铁工艺及计算,北京:冶金工业出版社,1991:339~359
[49] 刘云彩,张宗民,庄玉茹.首钢 2 号高炉专家系统的开发和应用.炼铁.1995,6(14):31~34
[50] 刘祥官,刘芳,蔡漳平等.济钢 350m~3 高炉的炼铁优化专家系统.钢铁,1999,34(增刊):154
[51] 戴嘉惠.鞍钢高炉异常炉况专家系统及应用.炼铁,1994,13(1):25~28
[52] 陈令坤.我国高炉专家系统开发的现状.炼铁,2001,20(4):30～34.
[53] 李家新等.预测马钢 4 号高炉难行的模式识别.华东冶金学院学报,1995,12(2):219~224
[54] 刘祥官,刘芳.高炉炼铁过程优化与智能控制模型,高校应用数学学报 A 辑,2001,16(4):462~470
[55] 王正光,周忠英,侯伯亨等.数据采集与处理.北京:国防工业出版社,1985:169~173
[56] 刘金琨,邓守强,田青等.高炉专家系统的数据采集与处理.东北大学学报(自然科学版),1996,17(5):485~489
[57] 王筱留.钢铁冶金学(炼铁部分).北京:冶金工业出版社,2000:220
[2] 毕学工.高炉专家系统的研究与开发㈠,炼铁,2000,19 ⑵ :50~53
[3] 毕学工.高炉专家系统的研究与开发㈡,炼铁,2000,19 ⑶ :50~55
[4] 新日本制铁.新日铁におけゐ高炉用主要モデルの绍介,计测と控制,1987
[5] 岩村忠昭.プロセスの状况の分类.计测と控制,1985
[6] Yoshio Tsunozaki, Atsuhisa Takekoshi, Kocich Hashimotoet., et al. An expert System for Blast Furnace Control at Works, Nippon Kokan Technical Report. 1987, (119)PP 1~8
[7] Akira Ichihara, Satoshi kasai, Hiromasa Yamamoto, et al. Expert GO-STOP System at Kawasaki’s MiZushima Works, Iron and Steel Engineer, 1998(5)
[8] Kawasaki Steel. GO-STOP System Applied to Blast Furnace. Ironmaking Proceeding,1997
[9] Shigonbu, Kobayshi. Knowledge Compilation and Refinement for Fault Diagnosis. IEEE Exepert,1991,(10):39~46
[10] Yasuo. Takashi S, Masaaki S, et al. Application of a self-learning function to an expert system for blast furnace heat control. ISIJ International,1990,30(2):111~117
[11] G..Brunnbauer, G.Kolb, F. Lssinger, et al. Current Status for Blast Furnace Operation by Closed- loop Expert System AT VA-STAHL, Mc Master Symposium, Hamilton/Canada, Mai, 1999
[12] M. Cross ,R. D. Gibson and J.T.Moon. Development and Validation of A Practical Theory to Describe Gas Flow Through the Blast Furnace. Seminar on Heat and Mass Transfer in Metallurgical Systems. Dubrovnik, Yugoslavia(1997)
[13] H. Zeisel. Mathem at Ische Modellierung and Numerische Simulation der Vorg nge im Hochofen. Doctor Thesis, University of Linz(1995). Published by University tsverlag Rudolf Trauner,Linz
[14] Haimi S, Inkala P, Kivijarvj. Advabces In the Application of Blast Furnace Control Models at Rautaruukkts Raahe Blast Furnace. 1992 Ironmaking Conference Proceedings. USA:1992,149~158
[15] Tetsuya Y, Toshirou S, et al. Blast Furnace operational system with the application of advanced go-stop system at mizushima a works, Proceedings of sixth international iron and steel congress.Nagoya:ISIJ,1990,364~371
[16] Hirata T, Ramamura K, Mormoto S, et al. Blast Furnace Operation System Using Neural Net Works And Knowledgebase. Proceedings of the Sixth International Iron and Steel Congress,Nagoya:ISIJ,1990,23~27
[17] Mcgraw K, Briggs K H. Knowledge Acquisition; Principles and Guidelines, New Jersey; Prentice Hall, Inc., 1998,11~13
[18] Hirsh H, Noordewier M. Using background knowledge to improve inductive learning. IEEE Expert,1994,9(5):3~6
[19] F. Lasinger, A. Klinger, M. Lehner. 奥钢联 Vairon 高炉自动化(专家系统)的应用及初步成果.钢铁,2002,37(12):9~13
[20] H. Druchenthaner, B. Sch rz M. Schaler. Vairon 高炉优化软件包——专家系统.钢铁,2000,35(8):13~17
[21] 周渝生,许祖泽.从拉赫钢铁厂看 21 世纪的高炉炼铁技术.宝钢科技,1998,2:54~59
[22] 戴术英. 高炉奥钢联林茨厂的应用. 昆钢科技,2002,1:20~23
[23] 张文新. 国内外高炉的生产现状及其发展趋向.钢铁钒钛,1997,18(2):35~43
[24] 毕学工.瑞典律勒欧厂 2 号高炉超强化冶炼的分析.炼铁,1994,13(6):28~32
[25] 毕学工.高炉过程数学模型及计算机控制,北京:冶金工业出版社,1996
[26] 毕学工.人工智能和专家系统在钢铁工业中的应用,武汉钢铁学院学报,1995,18(2):146~154
[27] 刘金琨等.高炉铁水硅含量的神经网络时间序列预报,钢铁研究学报,1996(3):63~66
[28] 刘金琨,邓守强.高炉热状态预测专家系统的设计及实现方法,东北大学学报(自然科学版),1995,16(5):473~477
[29] 刘金琨,王树青,张建明等.高炉实时控制专家系统存在的问题及其解决法,浙江大学学报(工学版),2000,34(6):613~618
[30] 陈令坤,汪勇,付连春等.高炉冶炼专家系统在炉型管理中的应用,钢铁,2000,35(9):5~9
[31] 郭宏飞,周伟.高炉异常炉况判断专家系统的设计与实现,东北大学学报(自然科学版),1995,18(2):178~182
[32] 朱敏,李兰滨.高炉热状态判断专家系统机器学习子系统的设计,钢铁研究学报,1997(增刊):7~10
[33] 陈亮.高炉炉底侵蚀状态数学模拟模型的研究:[硕士学位论文],沈阳东北大学,1997
[34] 钱亚平,卢鸣,张雷等.马钢 2500m~3 高炉网络互联及实时监控的实施,炼铁,2003(增刊):24~26
[35] 陈令坤,汪勇,付连春等.武钢 4 号高炉冶炼专家系统的应用概况,钢铁,1999(10),150~153
[36] 刘祥官,刘芳,刘元和等.等莱钢 1 号 750m~3 高炉智能控制专家系统,钢铁,2002,37(8):18~22
[37] 刘祥官,刘显著,蒋美华等.智能控制专家系统在莱钢高炉的应用,冶金自动化,2002(6):15~18
[38] 刘祥官,王义康.新临钢 380m~3 高炉专家系统的应用,炼铁,2003(2):24~26
[39] 高贤成,张国营,殷玉祥等.炼铁优化专家系统在济钢高炉上的应用,钢铁,2000,35(6):5~9
[40] 刘祥官,刘芳,李满喜等.炼铁优化专家系统在济钢高炉的应用,冶金自动化,2001(2):15~19
[41] 冯震, 董世泽 . 高炉专家系统在本钢五号高炉的应用, 本溪冶金高等专科学校学报,2003,5(4):29~31
[42] 朱子宗,邹德,沈勇玲.安钢 4 号高炉能量管理优化及预测系统研究,冶金能源,1998,17(6):3~5
[43] 安云沛,车玉满,刘方等.鞍钢 4 号高炉热状态专家系统的开发与应用,鞍钢技术,1997(8):6~11
[44] 王红章,袁万能,刘祥官.八钢 2#高炉专家系统的设计,新疆钢铁,1999(4):12~16
[45] 贾碧 , 施金良 , 余群威等 . 重钢 5 号高炉 综 合 诊 断专 家 系 统 的开 发与 应用 , 炼铁,2003,22(6):31~33
[46] 吴海刚,顾继雄,忻毅等.上钢一厂 2500m~3 炉专家系统的开发与应用,炼铁,2004,23(1):31~34
[47] 刘金琨,吴士杰,刘汉武等.高炉专家系统技术展望,钢铁研究学报,1997,9(3):59~62
[48] 成兰伯.高炉炼铁工艺及计算,北京:冶金工业出版社,1991:339~359
[49] 刘云彩,张宗民,庄玉茹.首钢 2 号高炉专家系统的开发和应用.炼铁.1995,6(14):31~34
[50] 刘祥官,刘芳,蔡漳平等.济钢 350m~3 高炉的炼铁优化专家系统.钢铁,1999,34(增刊):154
[51] 戴嘉惠.鞍钢高炉异常炉况专家系统及应用.炼铁,1994,13(1):25~28
[52] 陈令坤.我国高炉专家系统开发的现状.炼铁,2001,20(4):30～34.
[53] 李家新等.预测马钢 4 号高炉难行的模式识别.华东冶金学院学报,1995,12(2):219~224
[54] 刘祥官,刘芳.高炉炼铁过程优化与智能控制模型,高校应用数学学报 A 辑,2001,16(4):462~470
[55] 王正光,周忠英,侯伯亨等.数据采集与处理.北京:国防工业出版社,1985:169~173
[56] 刘金琨,邓守强,田青等.高炉专家系统的数据采集与处理.东北大学学报(自然科学版),1996,17(5):485~489
[57] 王筱留.钢铁冶金学(炼铁部分).北京:冶金工业出版社,2000:220