煤矿通风机远程故障监测系统的设计分析  

Research on the Method of Mine Fan Failure Prediction

作　　者：任孟林 Ren Menglin(Zhenchengdi Mine of Xishan Coal and Electricity Group Co.,Ltd.,Taiyuan Shanxi 030053)

机构地区：[1]西山煤电集团有限责任公司西铭矿,山西太原030053

出　　处：《机械管理开发》2021年第7期124-125,253,共3页Mechanical Management and Development

摘　　要：为了对矿井风机故障信息进行实时诊断,以风机振动信号为研究对象,利用小波降噪和HHT变化的方法对矿井风机的振动信号进行处理,并利用模糊神经网络理论建立了风机故障诊断系统,通过验证确定了故障分析系统的可行性,为矿山安全实现智能化提供借鉴。In order to diagnose the fault information of the mine fan in real time,this paper takes the vibration signal of the fan as the research object,uses wavelet de-noising and HHT change method to process the vibration signal of the mine fan,and establishes the fan fault diagnosis system by using the fuzzy neural network theory,and confirms the feasibility of the fault analysis system through verification,so as to realize the intelligent mine lifting mountain safety has made a certain contribution.

关 键 词：矿井风机 模糊神经 振动信号 故障诊断 

分 类 号：TD441[矿业工程—矿山机电]