电厂锅炉飞灰含碳量测量模型

Measurement model of unburned carbon for fly ash in utility boiler

目前广泛采用微波技术进行在线测量电厂飞灰含碳量,现场使用过程中飞灰成分变化对仪器的测量精度有严重影响。利用RBF神经网络对影响飞灰成分的多维数据和微波功率进行融合,建立电厂锅炉飞灰含碳量测量模型。该模型能够避免飞灰种类变化对飞灰含碳量测量结果的影响,提高了飞灰含碳量的测量精度。

Microwave technology is widely used nowadays for online measurement unburned carbon content in fly ash,however,fly ash type has great influence on its accuracy.RBF neural network is utilized to fuse the multi-parameter data of influence fly ash type and microwave power,measurement model of unburned carbon for fly ash in Utility Boiler is established.The measurement model can effectively prevent the fly ash type effect on the unburned carbon measurement,bring about enhancing measurement accuracy.