基于BP神经网络的矿井通风机故障诊断系统  

Fault Diagnosis System of Mine Ventilator Based on BP Neural Network

作　　者：王一兵[1,2] 

机构地区：[1]上海交通大学自动化系,上海200030 [2]中国煤炭科工集团上海研究院,上海200030

出　　处：《煤矿机电》2011年第4期59-61,共3页Colliery Mechanical & Electrical Technology

摘　　要：提出基于三层BP神经网络的诊断模型,提取反映矿井通风机故障信息的振动信号频谱特征,用来训练神经网络。实测证明矿井通风机故障诊断系统高效、准确,可以推广应用。Introduces a diagnosis model of tri-tier BP neural network and extracts characteristic spectra information reflecting fault of mine ventilator within different frequency ranges,which are used to train the network.The trial results show that the system is effective and accurate,and can be popularized.

关 键 词：BP神经网络 矿井通风机 特征提取 故障诊断 

分 类 号：TH432.1[机械工程—机械制造及自动化]