煤粉锅炉炉内二维温度场在线显示模型

An On-line Monitoring Model for the Two-dimensional Temperature Fields in the Pulverized Coal Boiler

将数值仿真技术与现代人工智能技术相结合,构建一个基于集成自适应神经网络的煤粉锅炉炉膛内特征截面上的二维温度场在线显示模型,以某热电厂DG130/9.8型四角切圆燃烧煤粉锅炉为应用实例,对模型进行检验,结果表明:该模型能够较准确地在线显示炉内温度分布状况,且具有精度较高(误差<5%)、运行速度较快(<2)、泛化能力强、鲁棒性好等特点;可以作为煤粉锅炉炉内燃烧状态在线监测与诊断的基础.

An on-line monitoring model, based on numeric simulation and the technology of adaptive fuzzy-neural network, was built for the two-dimensional temperature fields in the pulverized coal boiler. The model was built and checked up w^th a practical object, a DG130/9.8 tangential fired coal boiler in a power plant. The results show that the model can monitor the state of the temperature distribution in the furnace on-line with high precision（ less 5% ）, high calculate speed（ less 2 seconds）, good generalization and robust character. The model can be used to monitor the two-dimensional temperature fields and diagnose the combustion status in pulverized coal boiler as basic.