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轴流式通风机是煤矿生产中常用的关键设备， 对其进行故障诊断的研究具有十分重要的意义． 本文在分析通风机振动故障的原因及故障特征的基础上， 研究利用人工神经网络进行通风振动故障诊断的方法， 并建立了相应的神经网络诊断模型， 研究表明该模型可用于通风机的故障诊断， 是一种有效的智能分类器．
Axial fan is the key equipment commonly used in coal mine production, and it is very important to carry on fault diagnosis research. Based on the analysis of the causes and fault characteristics of ventilator vibration faults, this paper studies the method of diagnosing ventilation and vibration faults using artificial neural network and establishes the corresponding neural network diagnosis model. The results show that this model can be used to diagnose ventilator faults , Is an effective intelligent classifier.