电站锅炉炉内火焰局部光谱特征在线辩识煤种方法  

Online Identification Method of Coal Species in Power Plant Boiler Furnace Based on Local Flame Spectral Characteristics

作　　者：尹峰[1] 罗志浩[1] 孙坚栋[2] 周昊[1] 岑可法[1] 

机构地区：[1]浙江大学能源工程系,浙江省杭州市310027 [2]国网浙江省电力公司电力科学研究院,浙江省杭州市310014

出　　处：《中国电机工程学报》2016年第20期5530-5538,5729,共9页Proceedings of the CSEE

摘　　要：在电站锅炉燃烧闭环优化控制领域,炉内测量技术非常关键却发展较慢,对煤种的在线检测与辨识是其难点之一。文中提出了一种新的基于火焰发光机理特性的煤种在线辨识方法,采用光纤光谱仪获取关键波长火焰光谱数据,利用炉膛火焰中Na、K、Li这3种碱金属元素的共振谱线强度与其在燃煤中的含量存在一定对应关系的原理,通过光谱强度间相互关系的一系列特定算法变换,确定不同煤种的特征参量,实现煤种的在线辨识。算法规则消除了温度、煤粉浓度、空气系数、风速等的影响以及测量仪器与环境因素的引入干扰,系统简单可靠,可达到实时辨识。In the boiler burning closed loop optimization control field of the coal fired power plant, the technology of measurement in furnace is very key but develops slowly, and the online detection and identification of coal species is one of its difficulties. This paper proposed a novel coal species online identification method based on the flame glowing mechanism. Research shows that the resonance spectrum line strength has a definite relationship with the corresponding content of the element of Na, k, and Li alkali metal species in coal-fired flame. By means of a series of algorithm transformation around the strength relationship of the spectra, the characteristic parameter relevant to the specified coal species is achieved. Collected by the fiber spectrometer, the flame spectrum data in key wavelength area is used to identify the various kinds of coal online. The algorithm eliminates the temperature, concentration of coal particles, air ratio, wind speed and other influencing factors, and the introduction of interference of measuring instruments and the environment. The system is simple and reliable, can achieve real-time identification.

关 键 词：煤种 在线辨识 火焰发射光谱 碱金属原子光谱 谱线强度 

分 类 号：TK224[动力工程及工程热物理—动力机械及工程]