基于支持向量机与高斯分布估计的低NOx排放

燃烧优化的核心在于建立有效而快速的建模工具及寻优算法,以便于在线应用。为了研究新方法的适用性以及克服常用算法的缺点,本文利用支持向量回归建立了大型四角切圆燃烧电站锅炉NO_x排放特性模型。利用大量的热态实炉试验NO_x排放数据对模型进行了训练和验证。结果表明,支持向量回归模型能获得较神经网络模型更加准确的预测结果,相对于神经网络,支持向量回归能更好处理大样本量数据的非线性问题。随后,采用一种基于高斯概率密度 (GPDD)的分布估计优化算法对NO_x排放模型进行了寻优。研究发现,与遗传算法相比,GPDD具有更好的寻优能力与更快的收敛速度。结合支持向量回归与高斯概率密度分布(GPDD)算法能有效降低燃煤锅炉NO_x排放量,不到1 min的优化时间便于在线应用。研究结论可为该算法在实际电厂中推广应用提供参考依据。     

石油焦燃烧脱硫对NOx排放的影响

引言 石油焦是石油加工中获得的高沸点碳氢化合物经焦化后得到的最终产物.由于石油焦中的硫和重金属含量高,大多不适合作要求较高的化工和冶金工业的原料,只能作为燃料使用.美国Nisco热电厂410t*h-1纯烧石油焦循环床锅炉[1,2]的成功运行证明了循环流化床锅炉燃烧石油焦技术是先进和可靠的,经济上是可行的.采用循环流化床锅炉燃烧石油焦是今后石化企业解决石油焦出路的较好途径.     

石油焦燃烧脱硫对NOx排放的影响

引　言石油焦是石油加工中获得的高沸点碳氢化合物经焦化后得到的最终产物 .由于石油焦中的硫和重金属含量高 ,大多不适合作要求较高的化工和冶金工业的原料 ,只能作为燃料使用 .美国Nisco热电厂 4 10t·h- 1纯烧石油焦循环床锅炉[1,2 ] 的成功运行证明了循环流化床锅炉燃烧石油焦技术是先进和可靠的 ,经济上是可行的 .采用循环流化床锅炉燃烧石油焦是今后石化企业解决石油焦出路的较好途径 .由于石油焦中硫含量较高 ,一般燃烧石油焦都采用石灰石作为脱硫剂来脱硫 ,控制SO2 的排放 .石油焦燃烧污染物主要包括SO2 和NOx,也包括N2 O ,其排…     

旋流浓淡燃烧器中煤粉浓缩器对煤燃烧NOx生成的影响

应用数值模拟方法研究了旋流燃烧器中煤粉浓缩器对煤燃烧NO_x生成的影响,给出了热NO_x和燃料NO_x生成的详细信息.预报结果表明：采用作者研制的弱旋煤粉浓缩器后,可以大大地降低燃烧器出口区域燃料NO_x的生成,同时可以保持煤粉颗粒较高的燃尽率.模拟结果也表明,燃烧器出口区域的NO_x生成主要是由燃料NO_x的生成机理来控制,热NO_x在总NO_x的生成量中所占比例不大.因此,该旋流浓淡燃烧器具有高效低污染性能.     

旋流浓淡燃烧器中煤粉浓缩器对煤燃烧NOx生成的影响

应用数值模拟方法研究了旋流燃烧器中煤粉浓缩器对煤燃烧NO_x生成的影响，给出了热NO_x和燃料NO_x生成的详细信息.预报结果表明：采用作者研制的弱旋煤粉浓缩器后，可以大大地降低燃烧器出口区域燃料NO_x的生成，同时可以保持煤粉颗粒较高的燃尽率.模拟结果也表明，燃烧器出口区域的NO_x生成主要是由燃料NO_x的生成机理来控制，热NO_x在总NO_x的生成量中所占比例不大.因此，该旋流浓淡燃烧器具有高效低污染性能.     

O2/N2、O2/CO2和O2/CO2/NO气氛下煤粉燃烧NOx排放特性

利用滴管炉研究了O₂/N₂、O₂/CO₂和O₂/CO₂/NO气氛下煤燃烧过程中NO_x的排放特性。实验结果表明,在O₂/N₂和O₂/CO₂气氛下,高温或高O₂浓度均使NO排放量增加。O₂/CO₂气氛下NO排放量比O₂/N₂气氛下NO排放量低大约30%～40%。在O₂/CO₂/NO气氛下,温度不同时,O₂浓度变化对NO排放量的影响规律不同,对循环NO降解的影响规律也不同。高温不利于循环NO降解。随停留时间的延长NO排放量出现两个峰值。     

基于支持向量机回归的天然气负荷预测研究

Natural gas load forecasting is a key process to the efficient operation of pipeline network. An accurate forecast is required to guarantee a balanced network operation and ensure safe gas supply at a minimum cost. Machine learning techniques have been increasingly applied to load forecasting. A novel regression technique based on the statistical learning theory, support vector machines (SVM), is investigated in this paper for natural gas shortterm load forecasting. SVM is based on the principle of structure risk minimization as opposed to the principle of empirical risk minimization in conventional regression techniques. Using a data set with 2 years load values we developed prediction model using SVM to obtain 31 days load predictions. The results on city natural gas short-term load forecasting show that SVM provides better prediction accuracy than neural network. The software package natural gas pipeline networks simulation and load forecasting (NGPNSLF) based on support vector regression prediction has been developed, which has also been applied in practice.     

基于均匀设计与支持向量回归的发酵配方优化

结合均匀设计与支持向量回归,提出了一种新的配方优化实验设计与分析方法UD-SVR. 将其应用于优化产谷氨酸脱羧酶大肠杆菌诱变株的培养基配方与发酵条件,在考虑9因素时仅通过2轮28个实验,酶活性(吸光度OD630)即由初始的1.528高效提升至2.303,明显优于二次多项式偏最小二乘回归等经验风险最小参比模型. UD-SVR为多因素多水平配方优化实验设计与分析提供了一套预测精度高、指导性强、可解释性好、优化高效的整体解决方案.     

基于负荷划分数据和支持向量机的火电厂燃烧过程建模

为建立燃烧过程稳态模型,首先利用稳态检测算法提取稳态样本;针对稳态数据中的不均衡性,提出了一种基于负荷划分数据的方法,即根据负荷工况将样本划分成训练子集与测试子集,以提高模型的泛化性能。利用单因素图形分析方法确定3个模型参数的搜索范围,将网格搜索与交叉验证相结合选择最优的模型参数,在此基础上建立了一个300 MW燃煤火电厂机组锅炉燃烧过程的支持向量机模型,包括锅炉效率、NO_x排放量、排烟温度和飞灰含碳量4个过程输出。结果表明,经过参数优化的4个输出模型均具有很好的泛化性能。     

CO含量对烟气选择性非催化还原反应的影响

分别以氨水和尿素溶液作为还原剂,在管式反应器上详细研究了CO含量对烟气SNCR（选择性非催化还原）脱硝性能的影响。结果表明,CO含量增加导致：（1）SNCR脱硝温度窗口和最佳脱硝温度向低温方向移动,同时脱硝温度窗口宽度变窄、最大脱硝效率降低,尤其是以氨水作为还原剂时更为突出;（2）N₂O排放的峰值升高;当以尿素溶液作还原剂时,N₂O排放温度窗口主要向低温方向扩展;当以氨水作还原剂时,N₂O排放温度窗口向低温和高温两个方向扩展;（3）NH₃及HNCO残留量曲线向低温方向移动。维持相同的φ（CO）/φ（urea）,氨氮比增加将导致最佳脱硝温度略微降低。氨氮比或氧含量的变化对NO_x、N₂O、NH₃及HNCO的排放趋势没有影响。     

MnO_x/RHA催化氧化NO制备工艺优化

以稻壳灰(RHA)为载体,采用等体积浸渍法制备了MnO_x/RHA催化剂,在常压固定床反应器上,考察了制备条件对MnO_x/RHA催化氧化NO活性的影响,采用XRD、SEM、EDX和XRF等方法对催化剂特征及制备条件的影响进行了分析。通过对催化剂特征的分析发现,MnO_x主要以无定形颗粒状负载在RHA内表面和断面上;除煅烧时间外,制备条件对催化剂活性有显著影响。通过对催化剂及RHA表面微观形貌和组分的分析发现,随着煅烧温度升高,RHA表面MnO_x颗粒尺寸增大,MnO_x晶体含量增加,当煅烧温度由200℃上升到650℃时,MnO_x颗粒粒径由0.1μm增大到1.0μm。随着灰化温度升高,RHA表面结构由平板状向疏松蜂窝状和细丝状转变。     

Optimization of coal-fired boiler SCRs based on modified support vector machine models and genetic algorithms

An integrated combustion optimization approach is presented for the combined considering the trade offs in optimization of coal-fired boiler and selective catalyst reaction (SCR) system, to balance the unit thermal efficiency, SCR reagent consumption and NO_x emissions. Field tests were performed at a 160 MW coal-fired unit to investigate the relationships between process controllable variables, and optimization targets and constraints. Based on the test data, a modified on-line support vector regression model was proposed for characteristic function approximation, in which the model parameters can be continuously adapted for changes in coal quality and other conditions of plant equipment. The optimization scheme was implemented by a genetic algorithm in two stages. Firstly, the multi-objective combustion optimization problem was solved to achieve an optimal Pareto front, which contains optimal solutions for lowest unit heat rate and lowest NO_x emissions. Secondly, best operating settings for the boiler, and SCR system and air preheater were obtained for lowest operating cost under the constraints of NO_x emissions limit and air preheater ammonium bisulfate deposition depth.     

制备方法对低温NH_3-SCR脱硝催化剂MnO_x/TiO_2结构与性能的影响

采用浸渍法、沉积法以及共沉淀法制备了MnOx/TiO2催化剂。运用XRD、BET、FTIR、H2-TPR和总酸量等技术对催化剂进行了表征,发现以共沉淀法制备的MnOx/TiO2催化剂具有最大的比表面积、孔体积和总酸量,孔径分布最集中,MnOx可以在TiO2表面高度分散。NH3-SCR脱硝活性表明,共沉淀法制备的MnOx/TiO2催化剂脱硝活性最好,当Mn负载量为20%时,高空速(60000 h-1)下,催化剂于140℃时对NO去除率可达92.9%。     

Simultaneous data reconciliation and joint bias and leak estimation based on support vector regression

Process data measurements are important for process monitoring, control, optimization, and management decision making. However, process data may be heavily deteriorated by measurement biases and process leaks. Therefore, it is significant to simultaneously estimate biases and leaks with data reconciliation. In this paper, a novel strategy based on support vector regression (SVR) is proposed to achieve simultaneous data reconciliation and joint bias and leak estimation in steady processes. Although the linear objective function of the SVR approach proposed is robust with little computational burden, it would not result in the maximum likelihood estimate. Therefore, to ensure accurate estimates, the maximum likelihood estimate is applied based on the result of the SVR approach. Simulation and comparison results of a linear recycle system and a nonlinear heat-exchange network demonstrate that the proposed strategy is effective to achieve data reconciliation and joint bias and leak estimation with superior performances.     

Prediction of jet penetration depth based on least square support vector machine

Experiments to investigate the jet penetration depth were carried out. The jet penetration depth increases with the increase of spouting gas velocity, spouting nozzle diameter and carrier gas density, but decreases with the rise of the static bed height, particle density, particle diameter and fluidized gas rate. The intelligent model to predict the jet penetration depth has been established based on least square support vector machine and adaptive mutative scale chaos optimization algorithm. The prediction performance of the intelligent model is better than empirical correlations and neural network.     

基于最小二乘支持向量回归机的光管污垢特性预测

搭建了污垢实验系统以测得管壁温度和出、入口温度等参数,并将这些参数作为模型的输入变量,以污垢热阻值作为模型的输出变量,利用最小二乘支持向量回归机搭建了污垢预测模型,对光管的污垢特性进行了预测。一方面,通过与测量结果相比较,验证所搭建的模型是合理可行的;另一方面,通过对多次预测结果分析比较得出,该模型不但适用于流速、水浴温度、材质等参数为定值的情况,而且当这些参数发生改变时,该模型也是适用的。     

燃料稀释对传统型和高预热空气稀释型燃烧炉性能的影响的数值研究

This numerical study investigates the effects of using a diluted fuel (50% natural gas and 50% N2) in an industrial furnace under several cases of conventional combustion (air with 21% O2 at 300 and 1273 K) and the highly preheated and diluted air (1273 K with 10% O2 and 90% N2) combustion (HPDAC) conditions using an in-house computer program. It was found that by applying a combined diluted fuel and oxidant instead of their uncombined and/or undiluted states, the best condition is obtained for the estab-lishment of HPDAC’s main unique features. These features are low mean and maximum gas temperature and high radiation/total heat transfer to gas and tubes; as well as more uniformity of theirs distributions which results in decrease in NOx pollutant formation and increase in furnace efficiency or energy saving. Moreover, a variety of chemical flame shape, the process fluid and tubes walls tem-peratures profiles, the required regenerator efficiency and finally the concentration and velocity patterns have been also qualita-tively/quantitatively studied.