摘要
由于煤矿条件十分恶劣,煤矿通风机经常发生各种故障,应对煤矿通风机故障展开故障诊断研究。笔者采用小波和神经网络相结合的方法对煤矿通风机进行故障诊断,理论上表明该方法可以很好的对煤矿通风机进行故障诊断。
Because conditions are very poor in coal,coal fan frequently occurs fault,so we should start coal fault diagnosis.This paper use the combination of wavelet and neural network as an approach for mine fan fault diagnosis,study shows thatthe method can be a good surface for mine fan fault diagnosis in theory.
出处
《装备制造技术》
2012年第1期96-97,105,共3页
Equipment Manufacturing Technology
