基于小波阈值降噪方法风机监测信号的研究  

Research on Fan Monitoring Signal Based on Wavelet Threshold Noise Reduction Method

作　　者：张洪全[1] 郭继坤[1] 张子红[1] 

机构地区：[1]黑龙江科技大学电气与信息工程学院

出　　处：《煤矿机械》2014年第1期52-54,共3页Coal Mine Machinery

摘　　要：风机监测信号采集噪声问题非常严重,采取小波分析法进行去噪,该方法的关键就是阈值的选取和阈值的处理方法。对阈值处理函数和阈值选取形式进行了比较,并在MATLAB环境下进行仿真研究,结果表明软阈值函数启发式阈值小波降噪比较适合于风机监测信号的降噪处理。Noise is a serious problem for fan monitoring signal acquisition,this paper adopted wavelet analysis method to reduce noise.The key to this method are the selection and the processing method of threshold.The threshold processing function and threshold choice forms are compared,and conclusions are found in MATLAB simulation that soft threshold function heuristic threshold wavelet de-noising is better suited for fan noise reduction processing signal.

关 键 词：小波变换 风机监测 阈值函数 降噪 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]