煤粉炉局部结渣的故障诊断模型

水冷壁结渣是电站燃煤锅炉中的经常性故障，及时估计锅炉的结渣情况对提高锅炉运行的经济性、防止锅炉发生严重事故具有重要的意义。该文分析了可用于诊断该故障的主要特征参数，运用神经网络的方法建立了局部结渣故障诊断模型。计算结果表明，诊断迅速、结果准确。该方法简单，无需昂贵的诊断设备，有广泛的应用前景。

Fault diagnosing model of local slagging on water walls of pulverized coal-fired boilers

Local slagging faults of water walls of pulverized coal fired boilers are often occurred. It is very important to diagnose these faults immediately in order to improve the economy and safety of boilers. The main characteristic parameters being proper to diagnose the slagging faults were analysised. A model of local slagging fault diagnosis using a neural network method was presented. This neural network model was trained and tested using the parameters given by an mathematical model. The simulating results show that this method is characterized by fast and accurate diagnosis, and is easy and can be used widespreadly.