基于主分量和小波分析的煤矿主通风机故障诊断研究  

Research on Fault Diagnosis of Coal Mine Main Ventilator Based on Principal Component and Wavelet Analysis

作　　者：俞星[1] 尹洪胜[1] 张敏[1] 于宁宁[1] 刘秀英[2] 高飞[1] 

机构地区：[1]中国矿业大学信电学院,江苏徐州221008 [2]中国矿业大学机电学院,江苏徐州221008

出　　处：《煤矿机械》2010年第4期238-240,共3页Coal Mine Machinery

摘　　要：针对主通风机故障对煤矿安全生产构成的威胁,综合采用主分量分析和小波分析方法对主通风机进行故障诊断。论述了主分量分析和小波分析原理,建立了主通风机故障诊断数据处理模型。在此基础上利用Matlab对采集的振动信号进行仿真实验,结果表明:该方法能够准确判断煤矿主通风机的故障类型。In view of the main ventilator breakdown which threats the coal mine production safety, uses the main component analysis and the wavelet analysis method for fault diagnosis to the main ventilator. Elaborated the main component analysis and the wavelet analysis principle, has established the main ventilator failure diagnosis data processing model. Based on this carries on the simulation experiment using Matlab to the gathering vibration signal, the results show that this method can judge the coal mine main ventilator breakdown type accurately.

关 键 词：主分量 小波 通风机 故障诊断 

分 类 号：TD72[矿业工程—矿井通风与安全] TP277[自动化与计算机技术—检测技术与自动化装置]