基于SVM-Wavelet组合算法在矿井通风机故障预测中的应用  

Application on Fault Prediction of Mine Ventilator Based on SVM-Wavelet Fuse Together

作　　者：潘浩[1] 李振璧[1] 李琳[1] 陈艳艳[2] 

机构地区：[1]安徽理工大学电气与信息工程学院,安徽淮南232001 [2]安徽理工大学理学院,安徽淮南232001

出　　处：《煤矿机械》2014年第11期252-255,共4页Coal Mine Machinery

摘　　要：鉴于传统单一预测对非平稳信号处理不佳且滤波不足、预测精度不够等缺点,提出基于SVM-Wavelet组合算法对通风机进行故障预测,运用小波进行信号滤波和特征提取,结合SVM训练样本建立模型,最终在与Matlab无缝连接的Lab VIEW上位机软件中实现模型预测。In view of the poor performance of the traditional single prediction for non-stationary signal. While short of the filtering and insufficient for the prediction accuracy .This paper propose a strategy about the fault prediction to the ventilator based on the algorithm with the SVM and Wavelet fuse together. While signal filtering and feature extraction with the wavelet .Then training the sample to establish the model through the SVM. Finally implement the prediction by the seamless connection of host computer software of the LabVIEW and Matlab.

关 键 词：通风机 故障预测 SVM-Wavelet LAB VIEW 

分 类 号：TD441[矿业工程—矿山机电]