基于RBF神经网络的制粉系统故障诊断

Fault Diagnosis of the Coal Milling System Based on RBF

针对制粉系统的复杂性及对其运行状态难以判断的问题,从制粉系统运行机理出发,运用现场运行数据建立了用于制粉系统故障诊断的径向基函数(RBF)神经网络。仿真实验表明:利用该神经网络可以对制粉系统各种工况进行有效的诊断,并对提高制粉系统的安全经济运行具有指导意义。

It is difficulty to evaluate its operation in conventional way considering the complexity of the milling system. The paper establishes a RBF NN to diagnose the fault of the milling system,based on the principle of the milling system and the site operating data. Simulation of the neural network system shows that it can efficiently diagnose any kind of operation condition of the milling system. The system will be a very powerful tool for improving security and economy of milling system.