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机译:在中试炉中使用SVM和火焰发射光谱对煤和生物质进行共烧,从而在在线过程中进行在线掺混类型识别[?show [AQ = “ ” ID = “ Q1] ”?>
Zhejiang Univ, Inst Thermal Power Engn, State Key Lab Clean Energy Utilizat, Hangzhou 310027, Zhejiang, Peoples R China;
Rundian Energy Sci & Technol Co Ltd, Zhengzhou 450052, Henan, Peoples R China;
Zhejiang Univ, Inst Thermal Power Engn, State Key Lab Clean Energy Utilizat, Hangzhou 310027, Zhejiang, Peoples R China;
support vector machines; power engineering computing; bioenergy conversion; furnaces; coal; feature extraction; steam power stations; online blend-type identification; cofiring coal; biomass; ReliefF plus SVM method; support vector machine; flame emission spectrum; pilot-scale furnace; coal-fired power stations; combustion optimisation; flame feature extraction; alkali metals atomic excitation spectral intensities; spectral signals; ultraviolet signal; optimum sampling number; optimum feature vector;
机译:悬浮研究炉中生物质与煤共燃排放因子的确定
机译:生物质混燃发电系统的排放和炉膛出口气体温度分析
机译:生物质混燃发电系统的排放和炉膛出口气体温度分析
机译:1.5 MW中试炉中粉煤与85%煤/ 15%生物质共烧燃烧传热测量的比较
机译:混合,分级和炉温对煤和生物质-蔗渣共烧的影响。
机译:煤和生物质共烧发电的排放物和炉气温度
机译:开发一种用于最小化NOx排放和最大化碳利用的验证模型