【作者】 王成文；

【导师】 孙保民；

【作者基本信息】 华北电力大学（北京） ， 热能工程， 2004， 硕士

【摘要】 本文主要工作是在已经开发成功的高温对流受热面积灰监测的基础上，开发低温对流受热面积灰在线监测以及水冷壁局部结渣在线监测，来指导和优化吹灰过程。本文是依据电厂DAS系统的现有数据，结合长期以来的灰污变化情况，运用人工神经网络之BP网络，使之能够预测各种工况下的清洁受热面热流，最终求出灰污状况。在水冷壁结渣监测中，建立了膜式水冷壁温度计算模型，导出了一个水冷壁背火侧两点温度与水冷壁实际局部热流的数学关系，通过采集水冷壁背火侧两点温度，来实现局部结渣监测。基于上述理论基础，利用Visual C++这一强大的软件开发工具，成功开发了一套锅炉受热面灰污监测软件系统。更多还原

【Abstract】 In this paper, the main work is that developing a suit of on-line monitoring system of fouling on the low-temperature convection surface and local slagging on water wall surface, to guide and optimize the progress of sootblowing, on base of the successfully developed monitoring system of fouling on the high-temperature convection surface. In the monitoring means, taking advantage of the data from the DAS of the plant and the variation of fouling for a long time, we can make it predict the heat-flux of the clean surface in any conditions by applying NN (Neural Network), then acquire the condition of fouling. We build a computing temperature model of membrane water wall and educe the relation between the local heat-flux of water wall and temperature of the back of the water wall. We realize the local slagging monitoring of water wall by the way of collection the temperature. On the base of this theory, we successfully developed a suit of monitoring system of fouling and slagging.更多还原