基于模糊神经网络的风机故障诊断

Fault Diagnosis of Ventilators Based on Fuzzy Neural Network

风机是企业安全生产的关键设备,探讨有效的故障诊断方法有着实际意义。将故障树和模糊神经网络相结合,利用故障树信息和专家经验知识提取神经网络的训练数据,并应用在风机故障诊断中,实例证明此方法较其他分析方法更简明、有效。

The ventilators are one of the most important equipments for production and safety in various industries,so it is of practical significance to discuss the effective fault diagnosing methods. Presents a hybrid model,combining the fault tree with fuzzy neural network.In this approach, the fault tree information and expertise knowledge are employed to extract the neural network training datas. An illustrative example of ventilators demonstrates that the method is straight forward and the execution is faster than other fault analysis models.