现代电力2011，Vol.28Issue(4)：70-72,3.
基于声学测温与人工神经网络的炉膛结渣在线监测方法
The On-Line Monitoring of the Furance Slagging Based on Acoustic Pyrometry and Artificial Neural Network
邓喆 1李庚生 1安连锁 1沈国清 1张世平1
作者信息
- 1. 华北电力大学能源动力与机械工程学院,北京102206
- 折叠
摘要
Abstract
Through researching on a boiler furnace slagging,the on-line furnace heating surface slagging monitoring system based on acoustic pyrometry and artificial neural network is put forward. The method combines the non-contact temperature measuring tool, acoustic pyrometry device,with BP neural network. The acoustic pyrometry device can measure the furnace outlet gas temperature, which provides the precondition for the furnace slagging on-line monitoring. It can make use of BP neural network's nonlinear mapping calculation of the furnace ideal outlet gas temperature, and estimate slagging of the whole furnace with the pollution coefficient. To verify the method of flagging online calculation, the data of furnace ideal outlet gas temperatures from a power plant between on-line acoustic pyrometry and BP neural network prediction can meet the project requirement and the relative error is about 3％.关键词
结渣/声学测温/BP神经网络/在线监测/炉膛出口烟温Key words
slagging/ acoustic pyrometry/ BP neural network/ on- line monitoring/ furnace outlet gas temperature分类
信息技术与安全科学引用本文复制引用
邓喆,李庚生,安连锁,沈国清,张世平..基于声学测温与人工神经网络的炉膛结渣在线监测方法[J].现代电力,2011,28(4):70-72,3.
