基于预数值计算的煤粉锅炉燃烧监测与优化
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摘要
煤粉锅炉燃烧监测和优化,是在确保锅炉安全性的前提下,通过燃烧调整,达到提高燃烧效率和降低污染物排放的目标。本文以某电站300MW四角切圆燃烧煤粉锅炉为具体研究对象,深入分析了控制氮氧化物排放与降低飞灰可燃物含量之间的矛盾,采用预数值计算方法,研究煤粉锅炉燃烧监测和优化。探讨了把计算结果精确但耗时较长的数值计算方法,应用于锅炉燃烧监测和优化。为四角切圆燃烧煤粉锅炉燃烧监测和优化提供了一种有效的途径。具体研究内容及主要研究成果如下:
(1)应用预数值计算方法,对煤粉锅炉的燃烧特性进行研究。利用四角切圆燃烧煤粉锅炉专用数值计算软件COALFIRE,对锅炉28个运行工况进行了精确预数值计算,得到了锅炉燃用煤质、煤粉细度、锅炉负荷和二次风配风方式等参数变化对炉内温度、氧浓度、一氧化碳浓度、辐射受热面热负荷,特别是飞灰可燃物含量、氮氧化物释放的影响规律。计算结果与实际运行数据吻合良好,为实现锅炉燃烧监测和优化提供了比较精确的数据支持。
(2)以预数值计算结果作为训练样本,建立了基于支持向量机的锅炉燃烧工况预测模型。支持向量机算法的特点是能根据有限的样本信息,在模型的复杂性和学习能力之间寻求折衷,获得较好推广能力。利用该算法解决锅炉燃烧工况影响因素复杂,获得的工况样本数量有限的问题,实现锅炉燃烧工况的监测,并与实际运行数据对比,对模型进行了验证。结果表明所建模型对燃烧工况的变化响应灵敏,结果准确,能够满足燃烧监测的要求。
(3)采用因子分析法,对锅炉燃烧工况的评价指标进行降维,定义评价燃烧工况优劣的安全性、经济性和环保性因子,推导了各因子的计算式。在提取燃烧工况的公共因子后,通过计算燃烧工况的综合评价得分,进而建立燃烧工况评判模型,并结合具体工况进行验证,结果表明,基于因子分析法的燃烧工况评价模型,评价结果合理,可用于指导锅炉燃烧调整与优化。
(4)采用Visual Basic语言开发了基于预数值计算的四角切圆煤粉锅炉燃烧监测与优化系统,并进行了离线运行与测试。结果表明通过该系统能够实现对燃烧工况的监测和优化,为煤粉锅炉达到高效燃烧和低污染物排放的优化运行,提供了新的途径。
The combustion monitoring and optimization of pulverized coal utility boiler aims to improve the combustion efficiency and reduce the emission of pollutions on the premise of guaranteeing the safe operation of the boiler by the methods of adjusting the boiler operating parameters. A 300MW tangential pulverized coal-fired boiler was taken as a study case. The contradiction between the unburned carbon in fly ash and emission of nitrogen oxide was analyzed. The pre-numerical calculation method was used to study the combustion monitoring and optimization. The application of numerical calculation, which was accurate but time consuming on the boiler real-time combustion monitoring and optimization, was discussed. The method offered an effective way for the combustion monitoring and optimization. Concrete research contents and main results were as follows:
(1) The pre-numerical calculation was applied in the research of combustion characteristics in furnace. COALFIRE was used as an effective tool for numerical calculation of combustion and heat transfer of the tangentially pulverized coal-fired boiler. Total 28 operating conditions were calculated using COALFIRE. The influences of coal properties, pulverized coal size, boiler load and the distribution of secondary air to temperature, oxygen concentration and thermal load of radiation surfaces were discussed, with the emphasis on the variation of unburned carbon in fly ash and the released rule of nitrogen oxide. Compared with the actual operating data, the calculation result was accurate. Pre-numerical calculation offered the data base to the further work.
(2) Taking the pre-numerical calculation results as the training samples, the predict model of combustion monitoring was established based on the Support Vector Machine. The Support Vector Machine has the characteristics of splitting the difference between the complexities and learning ability of model based on the limited sample information. Therefore, the model could obtain better popularizing ability. It adapted to solving the combustion problems because getting the operating samples was difficult. Compared with the calculated data and the actual operating data, the results indicated that the model responded the changes sensitively and the calculation results were reasonable, which met the request of the combustion monitoring.
(3) The evaluation indexes of the combustion conditions were reduced using the factor analysis method. The security, economic and environmental factors were defined. The formula of each factors were deduced. After drawing the public factors, the combustion evaluation model was established by calculating the scores of different operating mode. The model was tested using the actual operating condition. The result showed that the model was reasonable. It can be used as a reference to direct the boiler combustion adjustment and optimization.
(4) The combustion monitoring and optimization system based on pre-numerical calculation was developed using Visual Basic. The result of off-line running test indicated that it could realize the combustion monitoring and optimization. It offered a new way for the combustion monitoring and optimization on tangentially pulverized coal-fired boiler.
(1)应用预数值计算方法,对煤粉锅炉的燃烧特性进行研究。利用四角切圆燃烧煤粉锅炉专用数值计算软件COALFIRE,对锅炉28个运行工况进行了精确预数值计算,得到了锅炉燃用煤质、煤粉细度、锅炉负荷和二次风配风方式等参数变化对炉内温度、氧浓度、一氧化碳浓度、辐射受热面热负荷,特别是飞灰可燃物含量、氮氧化物释放的影响规律。计算结果与实际运行数据吻合良好,为实现锅炉燃烧监测和优化提供了比较精确的数据支持。
(2)以预数值计算结果作为训练样本,建立了基于支持向量机的锅炉燃烧工况预测模型。支持向量机算法的特点是能根据有限的样本信息,在模型的复杂性和学习能力之间寻求折衷,获得较好推广能力。利用该算法解决锅炉燃烧工况影响因素复杂,获得的工况样本数量有限的问题,实现锅炉燃烧工况的监测,并与实际运行数据对比,对模型进行了验证。结果表明所建模型对燃烧工况的变化响应灵敏,结果准确,能够满足燃烧监测的要求。
(3)采用因子分析法,对锅炉燃烧工况的评价指标进行降维,定义评价燃烧工况优劣的安全性、经济性和环保性因子,推导了各因子的计算式。在提取燃烧工况的公共因子后,通过计算燃烧工况的综合评价得分,进而建立燃烧工况评判模型,并结合具体工况进行验证,结果表明,基于因子分析法的燃烧工况评价模型,评价结果合理,可用于指导锅炉燃烧调整与优化。
(4)采用Visual Basic语言开发了基于预数值计算的四角切圆煤粉锅炉燃烧监测与优化系统,并进行了离线运行与测试。结果表明通过该系统能够实现对燃烧工况的监测和优化,为煤粉锅炉达到高效燃烧和低污染物排放的优化运行,提供了新的途径。
The combustion monitoring and optimization of pulverized coal utility boiler aims to improve the combustion efficiency and reduce the emission of pollutions on the premise of guaranteeing the safe operation of the boiler by the methods of adjusting the boiler operating parameters. A 300MW tangential pulverized coal-fired boiler was taken as a study case. The contradiction between the unburned carbon in fly ash and emission of nitrogen oxide was analyzed. The pre-numerical calculation method was used to study the combustion monitoring and optimization. The application of numerical calculation, which was accurate but time consuming on the boiler real-time combustion monitoring and optimization, was discussed. The method offered an effective way for the combustion monitoring and optimization. Concrete research contents and main results were as follows:
(1) The pre-numerical calculation was applied in the research of combustion characteristics in furnace. COALFIRE was used as an effective tool for numerical calculation of combustion and heat transfer of the tangentially pulverized coal-fired boiler. Total 28 operating conditions were calculated using COALFIRE. The influences of coal properties, pulverized coal size, boiler load and the distribution of secondary air to temperature, oxygen concentration and thermal load of radiation surfaces were discussed, with the emphasis on the variation of unburned carbon in fly ash and the released rule of nitrogen oxide. Compared with the actual operating data, the calculation result was accurate. Pre-numerical calculation offered the data base to the further work.
(2) Taking the pre-numerical calculation results as the training samples, the predict model of combustion monitoring was established based on the Support Vector Machine. The Support Vector Machine has the characteristics of splitting the difference between the complexities and learning ability of model based on the limited sample information. Therefore, the model could obtain better popularizing ability. It adapted to solving the combustion problems because getting the operating samples was difficult. Compared with the calculated data and the actual operating data, the results indicated that the model responded the changes sensitively and the calculation results were reasonable, which met the request of the combustion monitoring.
(3) The evaluation indexes of the combustion conditions were reduced using the factor analysis method. The security, economic and environmental factors were defined. The formula of each factors were deduced. After drawing the public factors, the combustion evaluation model was established by calculating the scores of different operating mode. The model was tested using the actual operating condition. The result showed that the model was reasonable. It can be used as a reference to direct the boiler combustion adjustment and optimization.
(4) The combustion monitoring and optimization system based on pre-numerical calculation was developed using Visual Basic. The result of off-line running test indicated that it could realize the combustion monitoring and optimization. It offered a new way for the combustion monitoring and optimization on tangentially pulverized coal-fired boiler.
引文
[1]郝卫平,李琼慧,赵一农.我国电力弹性系数的现实意义.中国电力,2003,36(5): 8～10
[2]国家计委、科技部联合印发.中国的能源概况和能源需求预测.2002,5
[3]谢治国.新中国能源政策研究[博士学位论文].合肥:中国科学技术大学,2006
[4]张雷.中国一次能源消费的碳排放区域格局变化.地理研究,2006,25(1): 1～9
[5]梁金修.我国能源供需与新型工业化能源战略.宏观经济管理,2006(4):37～41
[6]董均华,徐向东.基于煤种辨识的锅炉燃烧优化系统.热能动力工程,2006,21(2):128～131
[7] Palmer C. Khesin M. Spence R. et al. Experience using combustion zone sensing and analysis tools to optimise combusiton in steam boilers burning (low-sulphur)PRB coal.VGB powertech,2002,82(11):60～64
[8]黄伟,李文军.W型火焰锅炉燃用低挥发份无烟煤的试验研究.动力工程,2005,25(6):813～819
[9]刘福国,韩小岗,王金枝,等.锅炉偏离设计煤种时的燃烧优化.华东电力2000,28 (10):10～12
[10]崔国圣MJA型煤质成份在线检测装置在电厂的应用.电站系统工程, 2005, 28(4): 45～46
[11]廖宏楷.风煤在线测量的锅炉燃烧优化系统.动力工程,2005,25(4):559～562
[12]武宝会,师建斌.乏气送粉锅炉风速与煤粉浓度测量技术研究.热力发电, 2002,31(3):21～24
[13]孙国刚,李静海.激光多普勒流动测量技术在颗粒流体两相流中的应用.中国粉体技术,1997,3(3):25～32
[14]袁竹林,卢作基.用传热法测量燃煤锅炉气力输送中煤流量的研究.燃烧科学与技术,1999,5(1):52～56
[15]陈鸿伟,杨中其,周志萍,等.基于风粉在线监测锅炉燃烧优化控制.锅炉技术,2005.36(6):36～38
[16]杨兴森,尹静,白静,等.乏气送粉锅炉一次风煤粉浓度的测量方法与应用.中国电力,2003,36(4):53～55.
[17]吴智群,郭怀保,师建斌.基于动量法的乏气送粉锅炉风粉在线监测系统及其在DCS上的实现.热力发电,2004,33(4):24～27
[18]杨兴森,尹静,白玉,等.用文丘里法测量风粉混合物的浓度和流量.仪器仪表学报,2005,增刊:121～122
[19] Reese. B. Optimization of the fuel to air ratio at single burners by an exactmeasurement of coal dust and air, VGB Powertech, 2006(86):64～66
[20] A Vikhansky, E. Bar-ziv, B. Chudnovsky, et al. Measurements and numerical simulations for optimization of the combustion process in a utility boiler. International Journal of Energy Research,2004,28(5):391～401
[21]刘泰生.燃尽风对炉内流动和燃烧过程影响的数值模拟.动力工程.2006,26(1):116～120
[22]程伟良,夏国栋,周茵,等.锅炉分级燃烧优化技术的研究.动力工程,2004,24(3):336～339
[23]张春发,赵宁,谢飞,等.基于最佳风煤比修正的燃烧优化控制.发电设备,2004,(1):87～89
[24]崔军,宋亚强,肖军等.分级风比率对降低NO x及锅炉燃烧的影响.能源研究与利用,2006,26(1):25～28
[25]李芳,燃煤锅炉分级燃烧过程的数值模拟[博士学位论文].大连:大连理工大学,2006
[26]刘泰生,周武,叶恩清.燃尽风对炉内流动和燃烧过程影响的数值模拟.动力工程,2006,26(1):116～120.
[27]李石湘.二次风配风方式对锅炉燃烧优化的影响.湖南电力,2003,23(2): 37～39
[28] Li Zhengqi, Sun Rui, Zhou Jue, et al. Numerical study on the effect of the Over-Fire-Air to the air flow and coal combustion in a 670 t/h wall-fired boiler. Fuel Processing Technology, 2006,87(4):363～371
[29] Fan Yuesheng, Zou Zheng, Gao Jubao, et al. Experimental research of rich oxygen content on improving combustion characteristics of pulverized coal. Journal of Xi'an Jiao tong University, 2006,40(1):18～21
[30]薛美盛,孙德敏,吴刚,等.工业锅炉在线燃烧优化.化工自动化及仪表.2001 28(5):25～27
[31]申丽,谷俊杰,杨建蒙.基于烟气氧含量软测量的锅炉在线燃烧优化.仪器仪表用户2005,12(4):91～92
[32] Li Jianqiang, Liu Jizhen, Niu Yuguang, et al. Online self-optimizing control of coal-fired boiler combustion system. TENCON 2004.(2004 IEEE Region 10 conference), 2004,4(11): 21～24
[33]裘立春,张建华.基于CO的燃煤锅炉燃烧优化.浙江电力.2005,24(3):10～12
[34]赵宁,曹洪涛,李晓金,等.基于O2和CO信号修正的燃烧优化控制.电力科学与工程.2004,(3):23～26
[35]周怀春,娄新生,肖教芳,等.炉膛火焰温度场图像处理试验研究.中国电机工程学报,1995,15(5):295～300
[36]薛飞,李晓东,倪明江,等.基于面阵CCD的火焰温度场测量方法研究.中国电机工程学报,1999,19(1):39～41
[37]王飞,卫成业,马增益,等.根据火焰图像测量煤粉炉横截面温度场的研究.中国电机工程学报,2000,20(7):40～43
[38]周怀春,娄新生,邓元凯,等.基于图像处理的炉膛燃烧三维温度分布检测原理和分析.中国电机工程学报,1997,17(1):1～4
[39]周怀春,韩曙东,盛峰,等.炉膛燃烧温度场三维可视化监测方法模拟研究.动力工程,2003,23(1):2154～2159
[40]娄春,韩曙东,刘浩,等.一种煤粉燃烧火焰辐射成像新模型.工程热物理学报,2002,(增刊):93～96
[41]贾涛,程强,韩曙东,等.一种火焰辐射图像探头和标定方法.热力发电,2002,31(5):23～25
[42]曾佳,娄春,程强,等.大型电站锅炉炉内三维燃烧温度场可视化实验研究.工程热物理学报,2004,25(3):523～526
[43]彭敏,缪楚雄.炉膛火焰图像数字技术在电厂锅炉燃烧优化控制中的应用中国电力,2003,36(10):34～37.
[44] Shimoda, M. Sugano, A. Kimura, T. Prediction method of unburnt carbon for coal fired utility boilerusing image processing technique of combustion flame. Energy Conversion, IEEE Transactions on,1990,5(4):640～645
[45] Woon Bo Baek, Sung Jin Lee, Seung Yeob Baeg,et al. Flame image processing and analysis for optimal coal firing of thermal power plant. Industrial Electronics, 2001. Proceedings, 2001,(2): 928～931
[46] R.Homma, J Y.Chen. Combustion process optimization by genetic algorithms: reduction of NO2 emission via optimal postflame process. Proc Combust Inst 28 2000: 2483～2489
[47] Jia Jianhu, Paul Sabiston, Ray Jonhnson. Nonlinear MPC for emission reduction and boiler combustion optimization. 15th Annual Joint ISA POWID / EPRI Controls and Instrumentation Conference and 48th Annual Power Industry Symposium, 2005,1:127～136
[48] S.S.S. Chakravarthy, A.K. Vohra and B.S. Gill, Predictive emission monitors (PEMS) for NOx generation in process heaters. Computers & Chemical Engineering, 2000, 23 (11/12 ):1649～1659
[49] Chu Jizheng, Shieh S. Constrained optimization of combustion in a simulated coal-fired boiler using artificial neural network. Model and Information Analysis, 2003, 82(2): 693～695
[50] Gamely C. H., Thompson S. A. Lumped parameter NOx emissions model for a coal-fired boiler of power station. Journal of Institute of Energy,2002,75(2) : 43- 46
[51]李文学,李慧,张德江,等.电厂锅炉燃烧优化控制系统的设计.光学精密工程,2007,12(2):240～243
[52]周昊,朱洪波,岑可法.基于Internet/Intranet的火电厂锅炉低NO x燃烧优化指导系统.热力发电.2003,32(2):8～11
[53]王培红李磊磊陈强,等.人工智能技术在电站锅炉燃烧优化中的应用研究.中国电机工程学报,2004,24(4):184～188
[54]孙龙彪.电站锅炉燃烧过程的在线监测及优化[硕士学位论文].北京:华北电力大学.2004
[55]高岩,龚至豪.锅炉燃烧系统的仿人智能控制.北京理工大学学报,2002,22(3):315～317
[56] Edmundo Vasquez, Sears Rodney. Combustion control techniques achieve 0.15 lb/MMBtu NO x levels without SCR. Power Engineering (Barrington, Illinois), 2003,107(1):39～42
[57]程新华,张庆国,付存山.电站煤粉锅炉燃烧设备改造及燃烧优化,山东电力技术.2004.(3):35～38
[58]罗智. 300MW锅炉燃烧器改造及改造效果.电站系统工程.2004,20(3):23～24
[59]何大方.大型锅炉燃烧优化调整.华东电力.2001,29(2):12～14.
[60]何滔,宋景慧,王力.1970t/h锅炉燃烧优化调整分析,吉林电力.2002.(4):10～13
[61]孙伟,魏铁铮,陈华桂.电站锅炉效率计算方法研究.电力情报,2002,(2):21～22
[62]阎维平,梁秀俊,陈宝康.基于在线检测数据的电站锅炉效率实时计算方法的研究.热能动力工程,2001,16(2):189～190
[63]杨劲,朱再兴,周孑民,等.火电厂入厂煤与入炉煤热值差原因分析.湖南电力, 2009,29(1):21～23
[64]陈强,王培红,李琳,等.电站锅炉飞灰含碳量在线软测量模型算法.电力系统自动化,2005,29(2):45～48
[65]李智,蔡九菊,郭宏.基于神经网络的电站锅炉飞灰含碳量软测量系统.节能技术,2004,22(4):6～7
[66]李智,蔡九菊,徐有宁,等.软测量技术在电站锅炉优化燃烧上的应用.过程工程学报,2004,4(6):549～553
[67]赵新木,王承亮,吕俊复,等.基于BP神经网络的煤粉锅炉飞灰含碳量研究.热能动力工程,2005,20(2):158～162
[68]戴莉,宋兆龙.锅炉烟道飞灰含碳量在线检测系统的研究.传感器技术,2004,23 (12):17～19
[69]陈宇,刘吉臻,张阔.电站锅炉燃烧经济性诊断模型的研究.电力科学与工程,2004,(4):8～10
[70]陈敏生,刘定平.电站锅炉飞灰含碳量的优化控制.动力工程,2005,25(4):545～549
[71]高小涛,黄晋苏.火电厂400t/h锅炉燃烧试验、优化及调整.电力建设,2005, 26(3):14～16
[72]赵虹,王红岩,翁善勇,等.锅炉飞灰含碳量异常偏高的试验研究.动力工程.2004,(06):785～788.
[73]黄少鹗.运用连续飞灰含碳量监测系统优化锅炉燃烧.电站辅机,2004, (1):34～38
[74] Robert Pieter van der LANs, Peter Glarborg, Kim Dam-Johansen, et al. Influence of coal quality on combustion performance. Fuel,1998,77(12):1317～1328
[75] Rui Afonso, George C, Dusatko, et al. Measurements of NOx emissions from coal boilers. Combustion Science and Technology.1993, 93(1):41～51
[76] LockWood F C, Mahmud T, Yehiya M. A. Simulation of pulverized coal test furnace performance. Fuel, 1998, 77(12):1329～1337
[77] Harding A W, Brown S D, Thomas K.M. Release of NO from the combustion of coal chars. Combustion and Flame, 1996, 107(4):336～350
[78]向军,王红,李敏,等.锅炉燃烧性能试验研究与数值模拟.动力工程,1999,(增刊):494～498
[79] Hartman Spliethoff, Ulrich Gruel, Helmut Rudiger, et al. Basic effects on NOx emissions in air staging and returning at a bench scale test facility. Fuel, 1996, 75(5):560～564.
[80]曾汉才.燃烧与污染.武汉:华中理工大学出版社,1993.
[81]王建国,徐志明,杨善让.空气预热器积灰在线监测模型.中国电机工程学报,2000,20(7):37～39.
[82]阎维平.电站锅炉回转式空气预热器积灰监测模型的研究.动力程,2002,22(2):1708～1710
[83] Richards G H, Slater P N, Harb.J.N. Simulation of Ash Deposit Growth in a Pulveriazed Coal-Fired pilot Scale Reactor. Energy&Fuels,1993,(7):774-781.
[84] Erickson T.A, Allan S.E, Mccollor D.P, et al. Modeling of Fouling and Slagging in Coal-Fired Utility Boilers. Fuel Processing Technology, 1995,(44): 155-171
[85] Thomas C Elliott. Monitoring power plant peHormance.Power,1991 (9):11-20
[86] Afgan N, Carvalho M.G, Coelho P. Concept of expert system for boiler fouling assessment. Applied thermal engineering. 1996,16(10):835～844
[87]阎维平. 300MW燃煤电厂锅炉积灰结渣计算机在线监测与优化吹灰.中国电机工程学报,2000,20(8):84～88
[88]阎维平,高正阳,姜平,等.300MW机组W型火焰锅炉燃烧调整试验研究.动力工程, 1999,19(1):23～26
[89]张良.300MW直流炉采用燃烧技术措施降低NOx排放量试验研究.中国电力, 1998,31(4): 12～14, 28
[90]郝卫东,郭新根,赵晴川,等.莱芜发电厂2号炉改造后优化调整试验研究.山东电力技术,1998,(2):54～57
[91]史习仁,张才根.大容量锅炉烟侧热力差和攻关研究成效.锅炉技术,1998, 29(3):1～8
[92]周力行著.湍流气粒两相流动和燃烧的理论与数值模拟.北京:科学出版社, 1994
[93]还博文编.锅炉燃烧理论与应用.上海:上海交通大学出版社,1999
[94]周以琳,高蒙.锅炉燃烧系统优化控制及实现方法.工业仪表与自动化装置,1998,(4).50～53
[95]徐军伟,宋兆龙.王磊.电站锅炉燃烧优化技术现状和发展动向.江苏电机工程,2005,24(3):6～7
[96]董清梅,张怀宇.一台35 t/h锅炉过热蒸汽超温及燃烧系统故障的改造.锅炉制造,2006,(1):21～23
[97]孙维兵.锅炉表面式减温器故障及对热电厂效率的影响分析.能源研究与利用, 2008,(5):32～33
[98]于建成.采用变频技术控制减温器温度.化工自动化及仪表,1999,26(2):52～53
[99]鲁翠荣. 1025t/h锅炉再热器微量喷水减温器泄漏原因及对策.华北电力技术, 2008,(5):43～45
[100]李斌,王增荣,高传美.对螺旋管式减温器的改进.山东机械, 2003,(4):57～58
[101]唐齐德,苗兴.火电厂减温器损坏的几种形式及其原因分析.热力发电,2001, 30(2):52～56
[102]支小和.600MW级机组煤粉锅炉设计计算:[博士学位论文].杭州:浙江大学, 2008.3
[103]熊谦逊.锅炉减温器裂纹探析.大氮肥, 2005,28(3):204～204
[104]钟永明.蒸汽锅炉表面式减温器的安全运行.工业锅炉,2001,(3).47～49
[105]魏兆龙,郭朝令,杨义波.煤种燃烧稳定性试验研究.锅炉技术,1999,30(10): 6～9
[106] Keerthi S S, Lin C J. Asymptotic behaviors of support vector machines with Gaussian kernel. Neural Computation, 2003,15(7):1667～1689
[107] Lin H T, Lin C J. A study on sigmoid kernels for SVM and the training of non-PSD Kernels by SMO-type methods.March 2003. http://www.csie.ntu.edu tw/cjlin/papers.html.
[108] Bernhard E, Isabelle M, Vapnik V N. A training algorithm for optimalmargin classifier.Proceeding of the fifth Annual ACM Work shop on Computational Learning Theory. Pittsburgh: Pennsylvania, United States, 1992:144～152
[109] Cortes C. Vapnic V.“Support-vector networks”machine,learnging,1995, 20(3):273～297
[110] Vapnic V N. The Nature of Statistical Learning Theory.New York: Springer Verlag, 1995
[111]北京锅炉厂译,苏联锅炉机组热力计算标准方法.北京:机械工业出版社.1976
[112]南京工学院,西安交通大学热能动力教研室.电厂锅炉原理.北京:电力工业出版社,1980
[113]清华大学电力工程系锅炉教研组编著,锅炉原理及计算.北京:科学出版杜,1979
[114]陈学俊,陈听宽.锅炉原理.北京:机械工业出版社,1981
[115]许晋源,徐通模.燃烧学.北京:机械工业出版社.1980
[116]华北电力学院.火电厂热力设备及系统.北京:电力工业出版社,1980
[117]范从振主编,锅炉原理.北京:水利电力出版社,1986
[118]樊泉桂,阎维平.锅炉原理.北京:中国电力出版社,2004
[119]马明金,周克毅,胥建群,等.煤粉锅炉炉膛传热分区段计算的一种改进方法.锅炉技术,2004,35(2):18～20
[120]董芃,洪梅,秦裕琨,等.煤粉锅炉炉膛燃烧,传热一维数学模型的研究.热能动力工程,1999,14(6):424～427
[121]洪梅,董芃,秦裕琨.大型煤粉锅炉炉膛传热分体式计算方法研究.哈尔滨工业大学学报,2000,32(3):90～94
[122]洪梅,董芃,秦裕琨.大型煤粉锅炉炉膛传热分体式计算方法及其可视化编程.电站系统工程, 2000,16(3):139～142.
[123]刘成全,温良英.平展流燃烧过程的传输特性研究.钢铁, 2000,35(4):57～61
[124]赵伶玲,周强泰.轩流燃烧器的稳燃及其结构优化分析.动力工程,2006,26(1):74～80
[125]赵铁成,徐伟勇.基于应力ANFIS模型的电站锅炉寿命控制.锅炉制造,2001, (3):4～8
[126]赵铁成,徐伟勇.基于自适应神经模糊系统模型的锅炉汽包应力在线计算与监测.上海交通大学学报, 2000,34(9):1245～1248
[127] Gayer M. Slavik, P. Hrdlicka F.Real-time simulation and visualization using pre-calculated fluid simulator states. Proceedings Seventh International Conference on Information Visualization 2003 - International Conference on Computer Visualization and Graphics Applications, 2003:440～445
[128] Vapnik V N. The Nature of Statistical Learning Theory.New York: Springer Verlag,1995,1
[129] Cortes C, Vapnik V. Support Vector Networks. Machine Learning, 1995(20):273～297
[130] Mozer M, Jordan M, Petsche T. Improving the Accuracy and Speed of Support Vector Learning Machines. Advances in Neural Information Processing Systems 9. Cambridge, MA: MIT Press,1997:375～381
[131] Gish H, Schmidt M. Text-Independent Speaker Identification. Signal Processing Magazine, IEEE, 1994,11:18～32
[132] Kumar V, Poggio T. Learning - Based Approach to Real Time Tracking and Analysis of Faces. In Proceedings of the Fourth International Conference on Automatic Face and Gesture Recognition, Grenoble, letante, 2000:96～101
[133] Jeffrey Huang, Xuhui Shao, Harry Wechsler. Face Pose Discrimination Using Support Vector Machines. Proceedings of 14th International Conference on Pattern Recognition.1998,(1):154～165
[134] Walavalkar L. Mohammad Yeasin, Anand M. Narasimhamurthy, et al.Support Vector Learning for Gender Classification Using Audio and Visual Cues. International Journal of Pattern Recognition and Artificial Intelligence, 2003,17(3): 417～439
[135] Mukherjee S.Classifying Microarray Data Using Support Vector Machines A Practical Approach to Microarray Data Analysis. Boston: Kluwer Academic, 2003:166～185.
[136] Kari L, Loboda A, Nebozhyn M, et al. Classification and Prediction of Survival in Patients with the Leukemic Phase of Cutaneous T Cell Lymphoma. J. Experimental Medicine, 2003, (11): 1477～1488
[137] Brown M, Lewis H G, Gunn S R. Linear Spectral Mixture Models and Support Vector Machines or Remote Sensing. IEEE Trans. Geosciences and Remote Sensing ,1998 ,38(5):2346～2360
[138] Vapnik, Vladimir, Golowich, et al. Support Vector Method for Function Approximation, Regression, Estimation, and Signal Processing. Advances in Neural Information Processing Systems 9. Cambridge, MA: MIT Press, 1997, 1281～1287
[139] Weston J. Gammerman A, Stitson M, et al. Support Vector Density Estimation. Advances in Kernel Methods: Support Vector Learning.Cambridge, MA:MIT Press.1999, 293～305
[140] Pascal Vincent, Yoshua Bengio. Kernel Matching Pursuit, Machine Learning, 2002,48 (1-3), 165～187
[141] Emilio Carrizosa, Belen Martin-Barragan, Dolores Romero Morales. Multi-group support vector machines with measurement costs, a biobjective approach. Discrete Applied Mathematics, 2008,156(6), 950～966
[142] Suykens J A K. Vandewalle, Moor B. D. Optimal Control by Least Squares Support Vector Machines. Neural Networks, 2001, 14(1):23～25
[143]周昊,朱洪波,曾庭华,等.基于人工神经网络的大型电厂锅炉飞灰含碳量建模.中国电机工程学报,2002,22(6):96～100.
[144]王国鹏,翟永杰,封官斌,等.模糊支持向量机在汽轮机故障诊断中的应用.华北电力大学学报, 2003(4):47～50
[145]刘向军.四角切向燃烧煤粉锅炉炉内燃烧过程的数值模拟.[博士学位论文].北京:清华大学,1997
[146]李长志.切圆燃烧锅炉炉内气固两相流动数值模拟及结渣研究:[硕士学位论文].哈尔滨:哈尔滨工业大学,2004
[147]赵坚行.燃烧的数值模拟.北京:科学出版社,2002:35～64
[148]范维澄,万跃鹏.流动及燃烧的模型与计算.合肥:中国科学技术大学出版社,1992
[149]赵泽光.300MW电站锅炉炉膛壁面热负荷分布的数值模拟:[硕士学位论文].保定:华北电力大学,2005
[150]刘亚芝.基于预数值计算的300MW煤粉锅炉燃烧工况优化研究:[硕士学位论文].保定:华北电力大学,2005
[151] COALFIER使用简介(Version 1.0-007).CANMET能源技术中心,2006,11
[152]杨金芳.支持向量回归在预测控制中的应用研究[博士学位论文].保定:华北电力大学,2007.4
[153]王春林.大型电站锅炉配煤及燃烧优化的支持向量机建模与实验研究[博士学位论文].杭州:浙江大学,2007.4
[154]林少宫.多元统计分析及计算程序.武汉:华中理工大学出版社,1988:183～209
[155]施永红.因子分析在机械未完全燃烧损失中的应用.华东电力,2002,20(3):12～14
[156]余建英.数据统计分析与SPSS应用.北京:人民出版社,2003
[157]施永红,云峰,魏铁铮.电站锅炉机械未完全燃烧热损失分析方法的研究.节能技术.2007,25(5):438～440
[158]谭荣波,梅晓仁.SPSS统计分析实用教程.北京:科学出版社,2007
[2]国家计委、科技部联合印发.中国的能源概况和能源需求预测.2002,5
[3]谢治国.新中国能源政策研究[博士学位论文].合肥:中国科学技术大学,2006
[4]张雷.中国一次能源消费的碳排放区域格局变化.地理研究,2006,25(1): 1～9
[5]梁金修.我国能源供需与新型工业化能源战略.宏观经济管理,2006(4):37～41
[6]董均华,徐向东.基于煤种辨识的锅炉燃烧优化系统.热能动力工程,2006,21(2):128～131
[7] Palmer C. Khesin M. Spence R. et al. Experience using combustion zone sensing and analysis tools to optimise combusiton in steam boilers burning (low-sulphur)PRB coal.VGB powertech,2002,82(11):60～64
[8]黄伟,李文军.W型火焰锅炉燃用低挥发份无烟煤的试验研究.动力工程,2005,25(6):813～819
[9]刘福国,韩小岗,王金枝,等.锅炉偏离设计煤种时的燃烧优化.华东电力2000,28 (10):10～12
[10]崔国圣MJA型煤质成份在线检测装置在电厂的应用.电站系统工程, 2005, 28(4): 45～46
[11]廖宏楷.风煤在线测量的锅炉燃烧优化系统.动力工程,2005,25(4):559～562
[12]武宝会,师建斌.乏气送粉锅炉风速与煤粉浓度测量技术研究.热力发电, 2002,31(3):21～24
[13]孙国刚,李静海.激光多普勒流动测量技术在颗粒流体两相流中的应用.中国粉体技术,1997,3(3):25～32
[14]袁竹林,卢作基.用传热法测量燃煤锅炉气力输送中煤流量的研究.燃烧科学与技术,1999,5(1):52～56
[15]陈鸿伟,杨中其,周志萍,等.基于风粉在线监测锅炉燃烧优化控制.锅炉技术,2005.36(6):36～38
[16]杨兴森,尹静,白静,等.乏气送粉锅炉一次风煤粉浓度的测量方法与应用.中国电力,2003,36(4):53～55.
[17]吴智群,郭怀保,师建斌.基于动量法的乏气送粉锅炉风粉在线监测系统及其在DCS上的实现.热力发电,2004,33(4):24～27
[18]杨兴森,尹静,白玉,等.用文丘里法测量风粉混合物的浓度和流量.仪器仪表学报,2005,增刊:121～122
[19] Reese. B. Optimization of the fuel to air ratio at single burners by an exactmeasurement of coal dust and air, VGB Powertech, 2006(86):64～66
[20] A Vikhansky, E. Bar-ziv, B. Chudnovsky, et al. Measurements and numerical simulations for optimization of the combustion process in a utility boiler. International Journal of Energy Research,2004,28(5):391～401
[21]刘泰生.燃尽风对炉内流动和燃烧过程影响的数值模拟.动力工程.2006,26(1):116～120
[22]程伟良,夏国栋,周茵,等.锅炉分级燃烧优化技术的研究.动力工程,2004,24(3):336～339
[23]张春发,赵宁,谢飞,等.基于最佳风煤比修正的燃烧优化控制.发电设备,2004,(1):87～89
[24]崔军,宋亚强,肖军等.分级风比率对降低NO x及锅炉燃烧的影响.能源研究与利用,2006,26(1):25～28
[25]李芳,燃煤锅炉分级燃烧过程的数值模拟[博士学位论文].大连:大连理工大学,2006
[26]刘泰生,周武,叶恩清.燃尽风对炉内流动和燃烧过程影响的数值模拟.动力工程,2006,26(1):116～120.
[27]李石湘.二次风配风方式对锅炉燃烧优化的影响.湖南电力,2003,23(2): 37～39
[28] Li Zhengqi, Sun Rui, Zhou Jue, et al. Numerical study on the effect of the Over-Fire-Air to the air flow and coal combustion in a 670 t/h wall-fired boiler. Fuel Processing Technology, 2006,87(4):363～371
[29] Fan Yuesheng, Zou Zheng, Gao Jubao, et al. Experimental research of rich oxygen content on improving combustion characteristics of pulverized coal. Journal of Xi'an Jiao tong University, 2006,40(1):18～21
[30]薛美盛,孙德敏,吴刚,等.工业锅炉在线燃烧优化.化工自动化及仪表.2001 28(5):25～27
[31]申丽,谷俊杰,杨建蒙.基于烟气氧含量软测量的锅炉在线燃烧优化.仪器仪表用户2005,12(4):91～92
[32] Li Jianqiang, Liu Jizhen, Niu Yuguang, et al. Online self-optimizing control of coal-fired boiler combustion system. TENCON 2004.(2004 IEEE Region 10 conference), 2004,4(11): 21～24
[33]裘立春,张建华.基于CO的燃煤锅炉燃烧优化.浙江电力.2005,24(3):10～12
[34]赵宁,曹洪涛,李晓金,等.基于O2和CO信号修正的燃烧优化控制.电力科学与工程.2004,(3):23～26
[35]周怀春,娄新生,肖教芳,等.炉膛火焰温度场图像处理试验研究.中国电机工程学报,1995,15(5):295～300
[36]薛飞,李晓东,倪明江,等.基于面阵CCD的火焰温度场测量方法研究.中国电机工程学报,1999,19(1):39～41
[37]王飞,卫成业,马增益,等.根据火焰图像测量煤粉炉横截面温度场的研究.中国电机工程学报,2000,20(7):40～43
[38]周怀春,娄新生,邓元凯,等.基于图像处理的炉膛燃烧三维温度分布检测原理和分析.中国电机工程学报,1997,17(1):1～4
[39]周怀春,韩曙东,盛峰,等.炉膛燃烧温度场三维可视化监测方法模拟研究.动力工程,2003,23(1):2154～2159
[40]娄春,韩曙东,刘浩,等.一种煤粉燃烧火焰辐射成像新模型.工程热物理学报,2002,(增刊):93～96
[41]贾涛,程强,韩曙东,等.一种火焰辐射图像探头和标定方法.热力发电,2002,31(5):23～25
[42]曾佳,娄春,程强,等.大型电站锅炉炉内三维燃烧温度场可视化实验研究.工程热物理学报,2004,25(3):523～526
[43]彭敏,缪楚雄.炉膛火焰图像数字技术在电厂锅炉燃烧优化控制中的应用中国电力,2003,36(10):34～37.
[44] Shimoda, M. Sugano, A. Kimura, T. Prediction method of unburnt carbon for coal fired utility boilerusing image processing technique of combustion flame. Energy Conversion, IEEE Transactions on,1990,5(4):640～645
[45] Woon Bo Baek, Sung Jin Lee, Seung Yeob Baeg,et al. Flame image processing and analysis for optimal coal firing of thermal power plant. Industrial Electronics, 2001. Proceedings, 2001,(2): 928～931
[46] R.Homma, J Y.Chen. Combustion process optimization by genetic algorithms: reduction of NO2 emission via optimal postflame process. Proc Combust Inst 28 2000: 2483～2489
[47] Jia Jianhu, Paul Sabiston, Ray Jonhnson. Nonlinear MPC for emission reduction and boiler combustion optimization. 15th Annual Joint ISA POWID / EPRI Controls and Instrumentation Conference and 48th Annual Power Industry Symposium, 2005,1:127～136
[48] S.S.S. Chakravarthy, A.K. Vohra and B.S. Gill, Predictive emission monitors (PEMS) for NOx generation in process heaters. Computers & Chemical Engineering, 2000, 23 (11/12 ):1649～1659
[49] Chu Jizheng, Shieh S. Constrained optimization of combustion in a simulated coal-fired boiler using artificial neural network. Model and Information Analysis, 2003, 82(2): 693～695
[50] Gamely C. H., Thompson S. A. Lumped parameter NOx emissions model for a coal-fired boiler of power station. Journal of Institute of Energy,2002,75(2) : 43- 46
[51]李文学,李慧,张德江,等.电厂锅炉燃烧优化控制系统的设计.光学精密工程,2007,12(2):240～243
[52]周昊,朱洪波,岑可法.基于Internet/Intranet的火电厂锅炉低NO x燃烧优化指导系统.热力发电.2003,32(2):8～11
[53]王培红李磊磊陈强,等.人工智能技术在电站锅炉燃烧优化中的应用研究.中国电机工程学报,2004,24(4):184～188
[54]孙龙彪.电站锅炉燃烧过程的在线监测及优化[硕士学位论文].北京:华北电力大学.2004
[55]高岩,龚至豪.锅炉燃烧系统的仿人智能控制.北京理工大学学报,2002,22(3):315～317
[56] Edmundo Vasquez, Sears Rodney. Combustion control techniques achieve 0.15 lb/MMBtu NO x levels without SCR. Power Engineering (Barrington, Illinois), 2003,107(1):39～42
[57]程新华,张庆国,付存山.电站煤粉锅炉燃烧设备改造及燃烧优化,山东电力技术.2004.(3):35～38
[58]罗智. 300MW锅炉燃烧器改造及改造效果.电站系统工程.2004,20(3):23～24
[59]何大方.大型锅炉燃烧优化调整.华东电力.2001,29(2):12～14.
[60]何滔,宋景慧,王力.1970t/h锅炉燃烧优化调整分析,吉林电力.2002.(4):10～13
[61]孙伟,魏铁铮,陈华桂.电站锅炉效率计算方法研究.电力情报,2002,(2):21～22
[62]阎维平,梁秀俊,陈宝康.基于在线检测数据的电站锅炉效率实时计算方法的研究.热能动力工程,2001,16(2):189～190
[63]杨劲,朱再兴,周孑民,等.火电厂入厂煤与入炉煤热值差原因分析.湖南电力, 2009,29(1):21～23
[64]陈强,王培红,李琳,等.电站锅炉飞灰含碳量在线软测量模型算法.电力系统自动化,2005,29(2):45～48
[65]李智,蔡九菊,郭宏.基于神经网络的电站锅炉飞灰含碳量软测量系统.节能技术,2004,22(4):6～7
[66]李智,蔡九菊,徐有宁,等.软测量技术在电站锅炉优化燃烧上的应用.过程工程学报,2004,4(6):549～553
[67]赵新木,王承亮,吕俊复,等.基于BP神经网络的煤粉锅炉飞灰含碳量研究.热能动力工程,2005,20(2):158～162
[68]戴莉,宋兆龙.锅炉烟道飞灰含碳量在线检测系统的研究.传感器技术,2004,23 (12):17～19
[69]陈宇,刘吉臻,张阔.电站锅炉燃烧经济性诊断模型的研究.电力科学与工程,2004,(4):8～10
[70]陈敏生,刘定平.电站锅炉飞灰含碳量的优化控制.动力工程,2005,25(4):545～549
[71]高小涛,黄晋苏.火电厂400t/h锅炉燃烧试验、优化及调整.电力建设,2005, 26(3):14～16
[72]赵虹,王红岩,翁善勇,等.锅炉飞灰含碳量异常偏高的试验研究.动力工程.2004,(06):785～788.
[73]黄少鹗.运用连续飞灰含碳量监测系统优化锅炉燃烧.电站辅机,2004, (1):34～38
[74] Robert Pieter van der LANs, Peter Glarborg, Kim Dam-Johansen, et al. Influence of coal quality on combustion performance. Fuel,1998,77(12):1317～1328
[75] Rui Afonso, George C, Dusatko, et al. Measurements of NOx emissions from coal boilers. Combustion Science and Technology.1993, 93(1):41～51
[76] LockWood F C, Mahmud T, Yehiya M. A. Simulation of pulverized coal test furnace performance. Fuel, 1998, 77(12):1329～1337
[77] Harding A W, Brown S D, Thomas K.M. Release of NO from the combustion of coal chars. Combustion and Flame, 1996, 107(4):336～350
[78]向军,王红,李敏,等.锅炉燃烧性能试验研究与数值模拟.动力工程,1999,(增刊):494～498
[79] Hartman Spliethoff, Ulrich Gruel, Helmut Rudiger, et al. Basic effects on NOx emissions in air staging and returning at a bench scale test facility. Fuel, 1996, 75(5):560～564.
[80]曾汉才.燃烧与污染.武汉:华中理工大学出版社,1993.
[81]王建国,徐志明,杨善让.空气预热器积灰在线监测模型.中国电机工程学报,2000,20(7):37～39.
[82]阎维平.电站锅炉回转式空气预热器积灰监测模型的研究.动力程,2002,22(2):1708～1710
[83] Richards G H, Slater P N, Harb.J.N. Simulation of Ash Deposit Growth in a Pulveriazed Coal-Fired pilot Scale Reactor. Energy&Fuels,1993,(7):774-781.
[84] Erickson T.A, Allan S.E, Mccollor D.P, et al. Modeling of Fouling and Slagging in Coal-Fired Utility Boilers. Fuel Processing Technology, 1995,(44): 155-171
[85] Thomas C Elliott. Monitoring power plant peHormance.Power,1991 (9):11-20
[86] Afgan N, Carvalho M.G, Coelho P. Concept of expert system for boiler fouling assessment. Applied thermal engineering. 1996,16(10):835～844
[87]阎维平. 300MW燃煤电厂锅炉积灰结渣计算机在线监测与优化吹灰.中国电机工程学报,2000,20(8):84～88
[88]阎维平,高正阳,姜平,等.300MW机组W型火焰锅炉燃烧调整试验研究.动力工程, 1999,19(1):23～26
[89]张良.300MW直流炉采用燃烧技术措施降低NOx排放量试验研究.中国电力, 1998,31(4): 12～14, 28
[90]郝卫东,郭新根,赵晴川,等.莱芜发电厂2号炉改造后优化调整试验研究.山东电力技术,1998,(2):54～57
[91]史习仁,张才根.大容量锅炉烟侧热力差和攻关研究成效.锅炉技术,1998, 29(3):1～8
[92]周力行著.湍流气粒两相流动和燃烧的理论与数值模拟.北京:科学出版社, 1994
[93]还博文编.锅炉燃烧理论与应用.上海:上海交通大学出版社,1999
[94]周以琳,高蒙.锅炉燃烧系统优化控制及实现方法.工业仪表与自动化装置,1998,(4).50～53
[95]徐军伟,宋兆龙.王磊.电站锅炉燃烧优化技术现状和发展动向.江苏电机工程,2005,24(3):6～7
[96]董清梅,张怀宇.一台35 t/h锅炉过热蒸汽超温及燃烧系统故障的改造.锅炉制造,2006,(1):21～23
[97]孙维兵.锅炉表面式减温器故障及对热电厂效率的影响分析.能源研究与利用, 2008,(5):32～33
[98]于建成.采用变频技术控制减温器温度.化工自动化及仪表,1999,26(2):52～53
[99]鲁翠荣. 1025t/h锅炉再热器微量喷水减温器泄漏原因及对策.华北电力技术, 2008,(5):43～45
[100]李斌,王增荣,高传美.对螺旋管式减温器的改进.山东机械, 2003,(4):57～58
[101]唐齐德,苗兴.火电厂减温器损坏的几种形式及其原因分析.热力发电,2001, 30(2):52～56
[102]支小和.600MW级机组煤粉锅炉设计计算:[博士学位论文].杭州:浙江大学, 2008.3
[103]熊谦逊.锅炉减温器裂纹探析.大氮肥, 2005,28(3):204～204
[104]钟永明.蒸汽锅炉表面式减温器的安全运行.工业锅炉,2001,(3).47～49
[105]魏兆龙,郭朝令,杨义波.煤种燃烧稳定性试验研究.锅炉技术,1999,30(10): 6～9
[106] Keerthi S S, Lin C J. Asymptotic behaviors of support vector machines with Gaussian kernel. Neural Computation, 2003,15(7):1667～1689
[107] Lin H T, Lin C J. A study on sigmoid kernels for SVM and the training of non-PSD Kernels by SMO-type methods.March 2003. http://www.csie.ntu.edu tw/cjlin/papers.html.
[108] Bernhard E, Isabelle M, Vapnik V N. A training algorithm for optimalmargin classifier.Proceeding of the fifth Annual ACM Work shop on Computational Learning Theory. Pittsburgh: Pennsylvania, United States, 1992:144～152
[109] Cortes C. Vapnic V.“Support-vector networks”machine,learnging,1995, 20(3):273～297
[110] Vapnic V N. The Nature of Statistical Learning Theory.New York: Springer Verlag, 1995
[111]北京锅炉厂译,苏联锅炉机组热力计算标准方法.北京:机械工业出版社.1976
[112]南京工学院,西安交通大学热能动力教研室.电厂锅炉原理.北京:电力工业出版社,1980
[113]清华大学电力工程系锅炉教研组编著,锅炉原理及计算.北京:科学出版杜,1979
[114]陈学俊,陈听宽.锅炉原理.北京:机械工业出版社,1981
[115]许晋源,徐通模.燃烧学.北京:机械工业出版社.1980
[116]华北电力学院.火电厂热力设备及系统.北京:电力工业出版社,1980
[117]范从振主编,锅炉原理.北京:水利电力出版社,1986
[118]樊泉桂,阎维平.锅炉原理.北京:中国电力出版社,2004
[119]马明金,周克毅,胥建群,等.煤粉锅炉炉膛传热分区段计算的一种改进方法.锅炉技术,2004,35(2):18～20
[120]董芃,洪梅,秦裕琨,等.煤粉锅炉炉膛燃烧,传热一维数学模型的研究.热能动力工程,1999,14(6):424～427
[121]洪梅,董芃,秦裕琨.大型煤粉锅炉炉膛传热分体式计算方法研究.哈尔滨工业大学学报,2000,32(3):90～94
[122]洪梅,董芃,秦裕琨.大型煤粉锅炉炉膛传热分体式计算方法及其可视化编程.电站系统工程, 2000,16(3):139～142.
[123]刘成全,温良英.平展流燃烧过程的传输特性研究.钢铁, 2000,35(4):57～61
[124]赵伶玲,周强泰.轩流燃烧器的稳燃及其结构优化分析.动力工程,2006,26(1):74～80
[125]赵铁成,徐伟勇.基于应力ANFIS模型的电站锅炉寿命控制.锅炉制造,2001, (3):4～8
[126]赵铁成,徐伟勇.基于自适应神经模糊系统模型的锅炉汽包应力在线计算与监测.上海交通大学学报, 2000,34(9):1245～1248
[127] Gayer M. Slavik, P. Hrdlicka F.Real-time simulation and visualization using pre-calculated fluid simulator states. Proceedings Seventh International Conference on Information Visualization 2003 - International Conference on Computer Visualization and Graphics Applications, 2003:440～445
[128] Vapnik V N. The Nature of Statistical Learning Theory.New York: Springer Verlag,1995,1
[129] Cortes C, Vapnik V. Support Vector Networks. Machine Learning, 1995(20):273～297
[130] Mozer M, Jordan M, Petsche T. Improving the Accuracy and Speed of Support Vector Learning Machines. Advances in Neural Information Processing Systems 9. Cambridge, MA: MIT Press,1997:375～381
[131] Gish H, Schmidt M. Text-Independent Speaker Identification. Signal Processing Magazine, IEEE, 1994,11:18～32
[132] Kumar V, Poggio T. Learning - Based Approach to Real Time Tracking and Analysis of Faces. In Proceedings of the Fourth International Conference on Automatic Face and Gesture Recognition, Grenoble, letante, 2000:96～101
[133] Jeffrey Huang, Xuhui Shao, Harry Wechsler. Face Pose Discrimination Using Support Vector Machines. Proceedings of 14th International Conference on Pattern Recognition.1998,(1):154～165
[134] Walavalkar L. Mohammad Yeasin, Anand M. Narasimhamurthy, et al.Support Vector Learning for Gender Classification Using Audio and Visual Cues. International Journal of Pattern Recognition and Artificial Intelligence, 2003,17(3): 417～439
[135] Mukherjee S.Classifying Microarray Data Using Support Vector Machines A Practical Approach to Microarray Data Analysis. Boston: Kluwer Academic, 2003:166～185.
[136] Kari L, Loboda A, Nebozhyn M, et al. Classification and Prediction of Survival in Patients with the Leukemic Phase of Cutaneous T Cell Lymphoma. J. Experimental Medicine, 2003, (11): 1477～1488
[137] Brown M, Lewis H G, Gunn S R. Linear Spectral Mixture Models and Support Vector Machines or Remote Sensing. IEEE Trans. Geosciences and Remote Sensing ,1998 ,38(5):2346～2360
[138] Vapnik, Vladimir, Golowich, et al. Support Vector Method for Function Approximation, Regression, Estimation, and Signal Processing. Advances in Neural Information Processing Systems 9. Cambridge, MA: MIT Press, 1997, 1281～1287
[139] Weston J. Gammerman A, Stitson M, et al. Support Vector Density Estimation. Advances in Kernel Methods: Support Vector Learning.Cambridge, MA:MIT Press.1999, 293～305
[140] Pascal Vincent, Yoshua Bengio. Kernel Matching Pursuit, Machine Learning, 2002,48 (1-3), 165～187
[141] Emilio Carrizosa, Belen Martin-Barragan, Dolores Romero Morales. Multi-group support vector machines with measurement costs, a biobjective approach. Discrete Applied Mathematics, 2008,156(6), 950～966
[142] Suykens J A K. Vandewalle, Moor B. D. Optimal Control by Least Squares Support Vector Machines. Neural Networks, 2001, 14(1):23～25
[143]周昊,朱洪波,曾庭华,等.基于人工神经网络的大型电厂锅炉飞灰含碳量建模.中国电机工程学报,2002,22(6):96～100.
[144]王国鹏,翟永杰,封官斌,等.模糊支持向量机在汽轮机故障诊断中的应用.华北电力大学学报, 2003(4):47～50
[145]刘向军.四角切向燃烧煤粉锅炉炉内燃烧过程的数值模拟.[博士学位论文].北京:清华大学,1997
[146]李长志.切圆燃烧锅炉炉内气固两相流动数值模拟及结渣研究:[硕士学位论文].哈尔滨:哈尔滨工业大学,2004
[147]赵坚行.燃烧的数值模拟.北京:科学出版社,2002:35～64
[148]范维澄,万跃鹏.流动及燃烧的模型与计算.合肥:中国科学技术大学出版社,1992
[149]赵泽光.300MW电站锅炉炉膛壁面热负荷分布的数值模拟:[硕士学位论文].保定:华北电力大学,2005
[150]刘亚芝.基于预数值计算的300MW煤粉锅炉燃烧工况优化研究:[硕士学位论文].保定:华北电力大学,2005
[151] COALFIER使用简介(Version 1.0-007).CANMET能源技术中心,2006,11
[152]杨金芳.支持向量回归在预测控制中的应用研究[博士学位论文].保定:华北电力大学,2007.4
[153]王春林.大型电站锅炉配煤及燃烧优化的支持向量机建模与实验研究[博士学位论文].杭州:浙江大学,2007.4
[154]林少宫.多元统计分析及计算程序.武汉:华中理工大学出版社,1988:183～209
[155]施永红.因子分析在机械未完全燃烧损失中的应用.华东电力,2002,20(3):12～14
[156]余建英.数据统计分析与SPSS应用.北京:人民出版社,2003
[157]施永红,云峰,魏铁铮.电站锅炉机械未完全燃烧热损失分析方法的研究.节能技术.2007,25(5):438～440
[158]谭荣波,梅晓仁.SPSS统计分析实用教程.北京:科学出版社,2007