供稿: 荆双喜;宋瑞菊 | 时间: 2019-07-04 | 次数: |
摘要: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.
基金:煤炭科学基金;
分类号:TD441
Fault Diagnosis of Ventilator Based on Neural Networks
Abstract:This paper presnts a method of fault diagnosis of ventilator based on neural networks.The vibration faults of ventilator are discussed, and the neural network model is set up.The working conditions and the faults of ventilator can be recognized by the neural work model.