基于径向基概率神经网络的高压加热器故障诊断

Fault diagnosis of high-pressure heater system based on radial basis probabilistic neural network

应用径向基概率神经网络实现高压加热器的故障诊断。介绍了RBPNN网络的结构和学习算法;总结了高加的故障集、征兆集和故障特征数据。在Matlab环境下给出了高加故障诊断的具体实例,表明该方法是一种可行有效的高加故障诊断方法。

A method based on radial basis probabilistic neural network （RBPNN） was applied to realize fault diagnosis of the high-pressure heaters in a power plant. The structure of the RBPNN and its learning algorithm was discussed in this paper. The fault sets, fault symptoms and fault feature data of the high-pressure heater system of a 300 MW power generating unit was summarized. Fault diagnosis examples of the high-pressure heater system under the environment of Matlab indicate that the method is effective and feasible.