多尺度小波分析在煤矿主通风机故障诊断中的应用
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摘要
快速傅里叶变换在信号分析中有着十分重要的作用,但传统的快速傅里叶变换无法分析通风机故障存在的趋势突变,故障的开始与结束等特征,而这些特征信号往往包含着故障的重要信息,同时,快速傅里叶变换对故障的局部信号分析也无能为力。为此,文中提出将多尺度小波理论与快速傅里叶变换相结合的方法,利用小波的"数学显微镜"特性,弥补快速傅里叶变换的不足,并将该方法应用于通风机故障诊断中,取得了良好的效果,试验表明,该方法可以有效地提高故障诊断的准确性。
The Fast Fournier Transform has a vital role in the signal analysis,but the traditional Fast Fournier Transform is unable to analyze the sudden change of tendency for the ventilator breakdown,breakdown start and stop characteristic.These characteristic signals are often containing important information of the breakdown.At the same time,it's also helpless for the Fast Fournier Transform to analyze the breakdown's partial signal.Therefore,the combined method of the multi-scaling wavelet theory and the Fast Fournier Transform is proposed.Using the characteristic of wavelet "mathematics microscope",make up the insufficiency of the Fast Fournier Transform,and apply this method in the ventilator failure diagnosis.The experimental results show the method can improve the accuracy of fault diagnosis.
The Fast Fournier Transform has a vital role in the signal analysis,but the traditional Fast Fournier Transform is unable to analyze the sudden change of tendency for the ventilator breakdown,breakdown start and stop characteristic.These characteristic signals are often containing important information of the breakdown.At the same time,it's also helpless for the Fast Fournier Transform to analyze the breakdown's partial signal.Therefore,the combined method of the multi-scaling wavelet theory and the Fast Fournier Transform is proposed.Using the characteristic of wavelet "mathematics microscope",make up the insufficiency of the Fast Fournier Transform,and apply this method in the ventilator failure diagnosis.The experimental results show the method can improve the accuracy of fault diagnosis.
引文
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[2]刘涛.实用小波分析入门[M].北京:国防工业出版社,2006.LIU Tao.The practical wavelet analysis entry[M].Beijing:National Defense Industry Press,2006.
[3]周伟.MATLAB小波分析高级技术[M].西安:西安电子科技大学出版社,2006.ZHOU Wei.MATLAB High technology wavelet analysis[M].Xi′an:Xi′an University of Electronic Science and Technology Press,2006.
[4]Mallat S,Zhang Q.Multidimensional wavelet frames[J].IEEE Trans signal Processing,1993,41(12):3397-3415.
[5]Newland D E.Wavelet analysis of vibration[J].Journal of Vibration and Acoustics Transactions of the ASME,1994(5):409-416,417-425.
[6]赵淑红,朱光明.用小波变换谱均衡法提高地震资料的分辨率[J].西安科技大学学报,2007,27(2):255-258.ZHAO Shu-hong,ZHU Guang-ming.Using combined method of wavelet transform and spectrum equalization to improve seis-mic data resolution[J].Journal of Xi'an University of Science and Technology,2007,27(2):255-258.
[7]Daubechies I,The wavelet transform,time-frequency localization and signal analysis[J].IEEETran.On IT,1990,36(5),961-1005.
[8]Lada E K.A Wavelet based procedure for process fault detection[J].IEEE Trans.On semiconductor Manufacturing,2001,(11):.
[9]李洪,蒋金泉.小波及奇异值分解在混沌特征计算中的综合去噪研究[J].西安科技大学学报,2006,26(3):306-310.LI Hong,JIANG Jin-quan.Eliminating noises of observation series using method of wavelet transform and strange value de-composition in course of calculation chaotic feature[J].Journal of Xi'an University of Science and Technology.2006,26(3):306-310.
[10]陈长征,杨璐.基于小波分析技术的通风机振动故障诊断研究[J].风机技术,1999,(6):34-36.CHEN Chang-zheng,YANG Lu.Ventilator vibration fault diagnosis based on wavelet analysis technology[J].Fan Technolo-gy,1999,(6):34-36.
[11]董长虹.Matlab小波分析工具箱原理与应用[M].北京:国防工业出版社,2004.DONG Chang-hong.Matlab wavelet analysis toolbox principle and application[M].Beijing:National Defense Industry Press,2004.
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