Abstract

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.

Full Text
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