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Instruction system for optimization lancing operation of boiler heating surface based on expert system

机译:基于专家系统的锅炉受热面优化采风作业指导系统

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In heat-engine plants, without optimization of structure designs, combustion behaviors and fuel categories, heating surfaces of heavy-duty boilers are polluted by ash in different levels in the course of operation; the effects of heat exchange are influenced greatly. So it is very important to clear ash away effectively and keep the regular states of heating surfaces in terms of working parameters and slag-bonding as well as operational demands. Based on artificial neural networks, a pollution monitoring model for heating surfaces of station boilers is presented, it fetches up the deficiency of traditional monitoring models, thus on-line monitoring of deposition and slagging of radiant heating surfaces such as furnace chamber and platen superheater in utility boilers is realized basically, also, it conduces to implement optimization lancing ulteriorly.
机译:在热力发电厂中,在没有优化结构设计,燃烧性能和燃料类别的情况下,重型锅炉的受热面在运行过程中会被不同程度的灰分污染;换热的影响很大。因此,有效清除灰分并保持工作表面,炉渣粘结以及操作要求方面的受热面规则状态非常重要。提出了一种基于人工神经网络的电站锅炉受热面污染监测模型,弥补了传统监测模型的不足,对炉膛,压板过热器等辐射受热面的沉积和结渣进行了在线监测。公用锅炉基本实现,也有利于实施优化融资。

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