小波分析在管道泄漏信号去噪中的优化研究
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摘要
为解决油气管道泄漏的实时发现、精确定位及事故处置问题,研究了小波分析在管道泄漏信号去噪中的优化方法,通过傅里叶变换与小波变换理论对比分析,选用了更具优越性的小波去噪方法。利用Matlab软件在软、硬阈值法下对信号处理结果进行二重仿真对比,结合小波基选取的一般原则,对5种常用小波函数进行了研究,分析了其数学特性和相应小波函数图的变化趋势。基于信噪比和均方根误差指标分析不同的去噪方法和分解尺度的去噪效果,综合提出了一种二重对比与三步寻优相结合的信号去噪方法。
To solve the real-time discovery,precise position and accident disposal of oil and gas pipeline leakage,the optimization method of wavelet analysis in denoising of pipeline leakage signal is studied.Through the theoretical comparison analysis of Fourier transform and wavelet transform,a more superior wavelet denoising method is selected.Two-stage numerical simulation comparison of the signal processing results is performed under the soft and hard threshold methods by using Matlab software.On the premise of combining the general principles of wavelet base selection,five common wavelet functions are studied,and the mathematical characteristics and the transformation trend of the corresponding wavelet function graph are analyzed.Based on the index of signal-to-noise ratio and root-mean-square error,a signal denoising method combining two-stage contrast and three-step optimization is proposed.
To solve the real-time discovery,precise position and accident disposal of oil and gas pipeline leakage,the optimization method of wavelet analysis in denoising of pipeline leakage signal is studied.Through the theoretical comparison analysis of Fourier transform and wavelet transform,a more superior wavelet denoising method is selected.Two-stage numerical simulation comparison of the signal processing results is performed under the soft and hard threshold methods by using Matlab software.On the premise of combining the general principles of wavelet base selection,five common wavelet functions are studied,and the mathematical characteristics and the transformation trend of the corresponding wavelet function graph are analyzed.Based on the index of signal-to-noise ratio and root-mean-square error,a signal denoising method combining two-stage contrast and three-step optimization is proposed.
引文
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[2]石玗,黄健康,樊丁,等.电弧声信号与铝合金MIG焊缝塌陷的相关性[J].机械工程学报,2007(10):32-35.
[3]司祯祯.傅里叶变换与小波变换在信号去噪中的应用[J].电子设计工程,2011(02):155-157.
[4]杨福生.小波变换的工程分析与应用[M].北京:科学出版社,1999.
[5]唐斌,董绪荣.小波多分辨率分析及其在自适应消噪中的应用[J].装备指挥技术学院学报,2007(01):75-78.
[6]韩宁,郑启宁.小波阈值去噪算法在信号处理中的应用与优化[J].战术导弹技术,2011(03):74-76.
[7]刘丽梅,刘齐跃,张静.基于小波变换模极大值的去噪方法研究[J].河北工业科技,2010,27(06):367-372.
[8]Li J,Cheng C,Jiang T,et al.Wavelet De-noising of Partial Discharge Signals Based on Genetic Adaptive Threshold Estimation[J].IEEE Transactions on Dielectrics&Electrical Insulation,2012,19(02):543-549.
[9]侯宁.基于小波分析的信号去噪方法[J].化学工程与装备,2009(08):137-138.
[10]Donobo D L.De-noising by Soft-threshoiding[J].IEEETransactions on Information Theory,1995,41(03):631-627.
[11]严亮.油气管道失效分析方法及其事故处置工程数据库管理系统研究[D].上海:上海理工大学,2018.