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工业锅炉是工业生产中普遍使用的动力设备,是能源转换的重要设备之一。工业锅炉的节能和正常运行与锅炉设计和燃烧控制有直接的关系。锅炉热效率是锅炉设计和运行中关键的技术指标。因此本文采用了人工神经网络对锅炉的飞灰含碳量特性进行了建模,并利用实炉测试试验数据对模型进行了校验,结果表明,人工神经网络能很好反映大型电厂锅炉各运行参数与飞灰含碳量特性之间的关系。
Industrial boilers are commonly used in industrial production of power equipment, energy conversion is one of the important equipment. The energy savings and normal operation of industrial boilers are directly related to boiler design and combustion control. Boiler thermal efficiency is a key technical indicator in boiler design and operation. Therefore, this paper used artificial neural network to model the carbon content of fly ash in boiler, and verified the model by using real furnace test data. The results show that artificial neural network can well reflect the operation of large power plant boilers Relationship between parameters and carbon content of fly ash.