基于神经网络的电站锅炉水冷壁积灰结渣监测模型的研究

Research of fouling and slagging Monitoring model of boiler waterwall at power station based on neural network

针对阜新电厂 2 0 0MW机组燃煤锅炉进行了多工况热态测试 ,获得了数据样本 ,运用BP神经网络和LM算法建立了电站锅炉水冷壁积灰结渣的监测模型。所建的神经网络监测模型 ,能够反映锅炉水冷壁积灰结渣的程度 ,为电站锅炉吹灰优化系统的开发打下了良好的基础。

The fouling and slagging of a 200MW unit′s burning coal boiler waterwall at Fuxin Power Plant is tested and data specimens have been gained. Taking BP neural network based on Levenberg-Marquardt(LM) algorithm, fouling and slagging monitoring model of boiler waterwall at power station is established. With the help of monitoring model based on neural network, fouling and slagging of the boiler waterwall can be known. It is contributed to make better base of developing soot-blowing optimization system.