新型矿用热风炉燃烧检测与控制系统的设计
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摘要
针对新型矿用热风炉燃烧控制的实际需求,提出了一套判断火焰燃烧状态并根据得出的判断结果调节阀门,从而保持热风炉相对正常燃烧的方法。该方法用PCA算法提取了最能够反应火焰燃烧状态的三个特征量,并将其作为BP神经网络的输入参数,根据经验值将得到的输出确定为火焰不同的燃烧状态,最后根据火焰不同的状态对煤气进气阀进行相应的调节。文章介绍了新型矿用热风炉燃烧检测与控制系统的软硬件组成,火焰燃烧状态判别算法及阀门控制方法。实验结果证明该系统可以有效地识别火焰燃烧状态并对阀门进行相应的控制,达到了预期要求。
Based on the practice requirement of the new mine environment hot stove’s combustion and controlling, the way to estimate combustion state of flame, and then adjust valves based on the last estimation which would keep normal combusting relatively of the hot stove was present. It picked up three character values which could furthest feedback combustion state of flame by PCA method, and then put them into BP Neural Network, it would get the flame’s combustion state from output values which compared with experience values. At last, it would adjust gas valves relatively based on the different combustion state. This paper introduces the hardware and software of new mine environment hot stove’s combustion detecting and controlling system, flame combustion state distinguishing arithmetic and valves controlling method. The experiment result proved that this system could recognize flame combustion state and control the gas valves effectively, which reached the first goal.
Based on the practice requirement of the new mine environment hot stove’s combustion and controlling, the way to estimate combustion state of flame, and then adjust valves based on the last estimation which would keep normal combusting relatively of the hot stove was present. It picked up three character values which could furthest feedback combustion state of flame by PCA method, and then put them into BP Neural Network, it would get the flame’s combustion state from output values which compared with experience values. At last, it would adjust gas valves relatively based on the different combustion state. This paper introduces the hardware and software of new mine environment hot stove’s combustion detecting and controlling system, flame combustion state distinguishing arithmetic and valves controlling method. The experiment result proved that this system could recognize flame combustion state and control the gas valves effectively, which reached the first goal.
引文
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[26]刘炜玮.Visual C++视频/音频实用工程案例精选.北京:人民邮电出版社,2004
[27]Gang Lu , Yong Yan , Mike Colechin. ADigital Imating Based Multifuntional Flam Monitoring System. IEEE Transactions on instrumentation and measurement,VOL.53,NO.4,AUGUST 2004:1152～1158
[28]陆其明.DirectShow开发指南.北京:清华大学出版社,2003
[29]宛延阎.C++语言和面向对象的程序设计.北京:清华人学出版社,1998
[30]谭浩强.C程序设计语言.北京:清华大学出版社,1991
[31]Nigel Quinnin.CodeGuru Visual C++编程精粹.北京:人民邮电出版社,2004
[32]潘爱民.COM原理与应用.北京:清华人学出版社,1999
[2]D.Sbarbaro, O.Farias, A.Zawadsky. Real-time monitoring and characterization of flames by principal component analysis. Combustion and Flame 132(2003) 591～595
[3]祖春光,周怀春,娄春,等.基于火焰图像的燃烧稳定性诊断和分析.湖北电力,2006(4) Vol.309 NO.2
[4]D.Sbarbaro, A.Zawadsky, O.Farias. Monitoring and characterization of combustion flames by Generalized hebbian learing. Combustion and Flame 132(2004) 421-425
[5]K.G.Anagnostakis, M.B.Greenwald, S.Ioannidis , et al. Flexible network monitoring with FLAM. Computer Networks 50 (2006) 2548～2563
[6]董晓峰,高庆忠,刘广生.基于BP网络的燃烧器火焰燃烧状态识别.东北电力学院学报,2005(2)Vol.25 No.1
[7]王天胜,李汉江,杨雪莲.高炉热风燃烧控制系统.武汉工程职业技术学院学报,2005(9)Vol.17 NO.3
[8]白卫东.站锅炉煤粉火焰安全监测及燃烧诊断方法研究:[博士学位论文].浙江大学机械与能源工程学院, 2004
[8]温良英,张生富,欧阳奇,等.高炉风口CCD成像监测系统的研制.重庆大学学报,2006(3) Vol.29 NO.3
[9]谢刚,王理飞,谢克明.基于火焰图像特征和粗糙集理论的燃烧诊断系统.测试技术学报,2006(9)Vol.20 NO.3
[10]徐伟勇.采用传像光纤和数字图像处理技术检测燃烧火焰.动力工程,1999,33(1):45～48.
[11]K.MHornik,M.Stinchcombe,H.White. Multilayer feedforward networks are universal approximators. Neural Network,Vol.2(5):359～366,1989
[12]杨宏昊,唐晓军,刘勇,等.基于火焰图像特征的神经网络诊断系统研究[J].应用科学学报,1998,16(1):81～87
[13]虞和济,陈长征,张省,等.基于神经网络的智能研究[M].北京:冶金工业出版社,2002
[14]饶文碧.用图像处理技术分析烟气中NOx含量[J].微机发展,1997,25(3):58～60
[15]卫成业,严建华,商敏儿,等.基于炉内火焰图像的燃烧诊断[J].动力工程,2003Vol .23No.3:2420-2427
[16]马晖,土飞,崔威,等.锅炉燃烧诊断和运行指导系统在300MW电厂锅炉上的应用[J].中国电力,2004,Vo1.37No.9: 30-34
[17]朱伟波.数字图像处理技术在锅炉燃烧诊断和优化中的应用.[硕士论文],2004
[18]Jones, B.R. Flame failure detection and modern boiler. J.Phys, E. sci. lnstrum.21 1988
[19]周怀春,韩才元.煤粉浓度和火焰颜色定量分析试验研究.中国工程热物理学会第八届年会1992
[20]Shimada, M. et al. Prediction method of unburnt carbon for coal fired utility boiler using image processing technique of combustion flame. IEEE Transaction on Energy Conversion, 5(4), 1990
[21]Chase, P.J, GR.Lovej oy. New scanner uses visible light to detect flame. Power Engineering, 86(4) 1982
[22]张嘉澎.火焰监视技术的发展.东北电力技术(副刊),1987(5) Vol,3 No.2
[23]王庆有,孙为珠.CCD应用技术.天津大学出版社,1993
[24]张晓舟,郭烨华,郑克哲.面阵CCD用于目标亮度的测量.应用光学,1995.16(2): 45～47
[25]刘长明,杨工明.Visual C++实践与提高(多媒体篇).北京:中国铁道出版社,2001
[26]刘炜玮.Visual C++视频/音频实用工程案例精选.北京:人民邮电出版社,2004
[27]Gang Lu , Yong Yan , Mike Colechin. ADigital Imating Based Multifuntional Flam Monitoring System. IEEE Transactions on instrumentation and measurement,VOL.53,NO.4,AUGUST 2004:1152～1158
[28]陆其明.DirectShow开发指南.北京:清华大学出版社,2003
[29]宛延阎.C++语言和面向对象的程序设计.北京:清华人学出版社,1998
[30]谭浩强.C程序设计语言.北京:清华大学出版社,1991
[31]Nigel Quinnin.CodeGuru Visual C++编程精粹.北京:人民邮电出版社,2004
[32]潘爱民.COM原理与应用.北京:清华人学出版社,1999