电站锅炉飞灰含碳量在线软测量模型算法  

Algorithm of On-line Soft Sensors Model of Carbon Content of Fly Ash in Coal-fired Boiler

作　　者：陈强[1] 王培红[1] 李琳[1] 冯泽磊[1] 

机构地区：[1]东南大学动力系,江苏省南京市210096

出　　处：《电力系统自动化》2005年第2期45-49,共5页Automation of Electric Power Systems

基　　金：国家自然科学基金(50376011)江苏省自然科学基金(BK2001005)

摘　　要：针对目前锅炉飞灰含碳量测量方法存在时间滞后和精度不高等问题，在分析对锅炉飞灰含碳量影响因素和做锅炉燃烧特性实验的基础上，建立了锅炉飞灰含碳量在线软测量的神经网络模型。算例表明该模型具有良好的泛化能力和敏感性，能正确描述电站锅炉飞灰含碳量的响应特性，可进一步推广使用。In view of the problems existing in the measurement of the carbon content of fly ash, such as time delay and poor accuracy, a neural network model is developed for on-line soft sensors based on an analysis of the influencing factors of the carbon content of fly ash in a coal-fired boiler and by combustion characteristics experiment. The calculating samples show that the proposed model has good generalization and sensitivity and is capable of correctly describing the carbon content of fly ash response characteristics of the coal-fired boiler and being extended for further applications.

关 键 词：锅炉 神经网络 软测量 飞灰含碳量 

分 类 号：TK31[动力工程及工程热物理—热能工程]