基于BP神经网络的超临界锅炉中间点温度预测.pdfVIP

学兔兔 第5期 锅 炉 制 造 No．5 2010年9月 BOILER MANUFACTURING Sep．2010 文章编号：CN23—1249(2010)05—0019—04 基于BP神经网络的超临界锅炉中间点温度预测 刘扬波 ，一，陈斌源 (1．武汉大学动力与机械学院，湖北武汉43007；2．广东珠海金湾发电有限公司，广东珠海519000) 摘 要：超临界锅炉中间点温度为控制主蒸汽温度的超前信号，同时也是水冷壁超温保护的重要参数，所以对 于中间点温度的仿真与预测具有重要意义。为了能够对中间点温度做出超前预测，提出了基于BP神经网络 的中间点温度预测新方法。通过对某600MW超临界锅炉生产数据进行仿真，验证了该方法的有效性。 ． 关键词：超临界锅炉；中问点温度；BP神经网路 中图分类号：TK223 文献标识码：A Forecasting the Temperature of Intermediate Points in Supercritical Boilers Based on BP——neural Network Liu Yangbo ，Chen Binyuan (1．School of PowerMechanical Engineering，Wuhan University，Wuhan 430072，China； 2．Guangdong Zhuhai Jinwan Power Generation Co．Ltd．，Zhuhai 519000，China) Abstract：Temperature at intermediate points in supercritical boilers is the ahead——signal for control·· ling main——steam temperature and the significant parameter for preventing over temperature in water — wal1．It is crucial for simulating and controlling temperature at intermediate points．As well as to Predictiv the temperature of intermediate points，the new method based on BPNN is brought forward to forecasting the temperature of intermediate points．The effectiveness of the proposed calculation method has been vindicated by the simulation of a certain 600 MW supercritical boilers’production data． Key words：supercritical boilers；temperature at intermediate points；BPNN 型描述。实际中通过试验调节水煤比来粗调控制 0 引 言 中间点温度的，而不同机组负荷对应不同的中间 超临界锅炉中间点温度为水冷壁出口汽水分