锅炉燃烧性能优化模型的建立  

ESTABLISHMENT OF COMBUSTION PERFORMANCE OPTIMIZATION MODEL FOR BOILERS

作　　者：李智[1] 蔡九菊[2] 赵殿瑞[1] 裴振英[1] 于贵君[1] 

机构地区：[1]沈阳工程学院技术经济系,辽宁沈阳110036 [2]东北大学热能工程系,辽宁沈阳110006

出　　处：《热力发电》2012年第3期62-65,共4页Thermal Power Generation

基　　金：辽宁省自然科学基金资助项目(20052097)

摘　　要：基于在线学习RBF网络模型,建立了1种用于锅炉燃烧性能优化的模型。经网络模型初始化、误差在线检测和在线学习,实现了模型与锅炉燃烧特性的实时匹配。当锅炉燃烧特性发生变化时,将激活RBF网络隐层的休眠节点,并以新的学习样本作为新增工作节点的中心,根据锅炉最新燃烧过程的数据在线快速修正燃烧性能模型。以某亚临界300MW供热机组为例,建立了锅炉燃烧性能模型并预测锅炉燃烧效率,其结果与实际运行结果吻合较好。Based on the online learning RBF network model, a combustion performance optimization model used for boilers has been established. Through initiation of the network model, on - line detection of errors,and on - line learning, the real - time matching of the model with the combustion performance in boilers has been realized. When the combustion performance in boiler is changing, the dormant nodes in hidden level of RBF network will be activated,and take new learning sample as the center of newly added working nodes, the combustion performance model will be rapidly corrected according to the newest data on - line in the combustion process of boiler. Taking subcritical 300 MW unit for heatsupply as example, the combustion performance model of boiler has been established, and the combustion efficiency of boiler being predicted, it tallies better with the result of practical operation.

关 键 词：锅炉 燃烧性能 RBF网络 燃烧效率 优化模型 

分 类 号：TK227[动力工程及工程热物理—动力机械及工程]