煤气鼓风机故障诊断的神经网络模型研究与实现

ON NEURAL NETWORK MODEL FOR GAS FAN FAULT DIAGNOSIS AND ITS IMPLEMENTATION

针对煤气鼓风机的故障特点,提出了一种基于BP神经网络的故障诊断方法。通过大量的模拟数据实验研究建立了神经网络故障诊断模型,并且实现了算法的编程,利用典型的故障数据对神经网络进行了训练,最后采用煤气鼓风机的实际工作数据验证了网络的有效性和准确性。

After studying the fault features of gas fan,the method of fault diagnosis for gas fan based on BP neural network is introduced in this paper.The model of BP neural network fault diagnosis was built up after studying on the examination result of lots of simulation data.The programming of the algorithm has been implemented as well.Typical data was used to train the BP neural network.In the end,the effectiveness and the accuracy of the network was verified by the data of gas fan in practical working conditions.