首页 | 本学科首页   官方微博 | 高级检索  
     

基于专家系统的锅炉燃烧系统优化控制
引用本文:高岩.基于专家系统的锅炉燃烧系统优化控制[J].电力自动化设备,2005,25(5):27-29,33.
作者姓名:高岩
作者单位:北京理工大学,信息科学技术学院,北京,100081
摘    要:根据炉膛温度更能快速反映煤的燃烧热效率,一定的煤量燃烧最充分时其温度也最高的原理,提出了一种由专家控制系统根据不同的燃烧工况提供最佳鼓风量方法,专家系统瓶颈问题的知识获取则由改进遗传算法优化完成。为了避免作为随机搜索的遗传算法在搜索过程中引起鼓风量的混乱,寻优过程离线进行,寻优结果数据提供给专家系统,最后由专家系统提供最佳鼓风量。该系统现场运行正常,通过锅炉燃烧效率测试热效率提高2.6%。

关 键 词:锅炉燃烧  鼓风量  专家系统  神经网络  遗传算法
文章编号:1006-6047(2005)05-0027-03

Optimal control of boiler combustion system based on expert system
GAO Yan.Optimal control of boiler combustion system based on expert system[J].Electric Power Automation Equipment,2005,25(5):27-29,33.
Authors:GAO Yan
Abstract:The furnace temperature can fleetly reflect the combustion thermal efficiency of coal and the temperature is highest when coal burns most sufficiently, based on which, a method with optimal air blowing quantity offered by expert system in accordance with different combustion conditions is proposed. The knowledge acquisition, as the bottleneck of expert system, is completed using an improved genetic algorithm optimization. To avoid air-blowing confusion during the random search of genetic algorithm, the optimization seeking is processed off-line and the optimal results are fed to expert system, with which expert system decides the optimal air blowing quantity. The system operations normally on site and enhances the heat efficient by 2.6%.
Keywords:boiler combustion  air blowing quantity  expert system  neural network  genetic algorithm
本文献已被 CNKI 维普 万方数据 等数据库收录!
点击此处可从《电力自动化设备》浏览原始摘要信息
点击此处可从《电力自动化设备》下载全文
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号