非线性动力学中特征尺度的分析及对双圆柱绕流的研究
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摘要
实验信号在采集过程中往往会遇到噪声干扰问题,噪声信号不仅会与信号中的有用部分混淆在一起,而且会影响到信号的处理结果和分析判断。本文提出在对实验数据进行处理分析之前对信号进行预处理,去除信号中含有的噪声信号、干扰信号和小能量尺度信号。基于EMD原理的应用,本文提出三次样条的EMD滤波降噪方法。通过与小波包降噪的效果相比较发现:EMD滤波降噪方法可以自适应地去除噪声,并达到比小波包降噪更好的降噪效果,具有更加精确的局部分析能力;针对传统的信号处理方法在去除干扰信号时,会造成与干扰信号处于同一频率尺度上的有用信号的损失这一问题,本文提出从能量尺度出发,有效地去除了信号中的干扰信号,保留了信号同一频带上的有用信息:双圆柱绕流的尾流场存在不同能量尺度的涡结构,而EMD方法是基于信号本身特有特征尺度分解信号的。本文利用EMD方法的这一特点,对尾流场的大涡结构进行了磨光处理,有助于分析判断尾流场中大涡的时空变化。
实验是研究双圆柱绕流的重要手段和方式,如何从大量的双圆柱绕流实验数据里提取更多的有用信息,以揭示绕流的一些内在机理,帮助人们加深对绕流本质的理解就显得尤其重要。本文通过频域分析和时-频分析两种方法对并列双圆柱绕流实验数据进行了气、固同步处理,对尾流场中不同位置的涡街变化规律从能量幅值角度作了分析和描述。
传统的数值模拟方法研究双圆柱绕流大都是从时域分析的尺度出发,本文利用Fluent软件,按1:1比例对双圆柱绕流进行三维建模和数值模拟,通过设置监控点采集动态模拟信号,进而对模拟信号进行了频域分析和时-频分析,相对于时域分析,可以更有效地掌握尾流场中不同能量尺度涡结构的时空变化规律,通过与实验结果比较分析,有助于寻找实验信号中的有用部分,对边界层分离、旋涡脱落等复杂流动现象可以更为直观地分析研究。
The disturbance noise is always existence in data acquisition, which would be confused with the usable signal and influence the analysis and the research. We propose the pretreatment of the signal before the time-frequency analysis and frequency analysis in this paper. Over the applications of the EMD-based, we reduced the noise by self-adapted filtering. Compared with the wavelet packets, the EMD-based method has more accurate analysis in local region. The tradition signal processing method would also lose the usable signal in the same frequency region when removing the disturbing signal. We propose to remove the disturbing signal in the energy characteristic scale, which could keep the usable signal. Because of the existence of the different energy-scale in the flow distribution, we also propose to polish the large-scale eddies. Since the EMD method proposes the signal based on the self-characteristic-scale of the signal, we polish eddies in the EMD method, which could help us to analyze the movement regular of the large eddies.
The experiment is an important method to research the circular cylinders. In order to find more valuable information to reveal the mechanism of the flow, we process the gas-solid synchronization signals by time-frequency analysis and frequency analysis method. We also analyze and describe the regular of eddies changing in the flow distribution from the energy characteristic scale.
The tradition numerical simulation researches the circular cylinders from the time analysis, which could show us the directly phenomenon. In this paper, we advanced the three-dimensional numerical simulation, based on the LES method of Fluent. We measured the gas fluctuating velocity and the solid fluctuating pressure by means of setting up the surface point. The simulation data would be also processed by time-frequency analysis and frequency analysis method. By comparing the experimental result and the simulation result, we could find the flow regular in different region, pick up the usable signal and grasp the regular of eddies changing.
实验是研究双圆柱绕流的重要手段和方式,如何从大量的双圆柱绕流实验数据里提取更多的有用信息,以揭示绕流的一些内在机理,帮助人们加深对绕流本质的理解就显得尤其重要。本文通过频域分析和时-频分析两种方法对并列双圆柱绕流实验数据进行了气、固同步处理,对尾流场中不同位置的涡街变化规律从能量幅值角度作了分析和描述。
传统的数值模拟方法研究双圆柱绕流大都是从时域分析的尺度出发,本文利用Fluent软件,按1:1比例对双圆柱绕流进行三维建模和数值模拟,通过设置监控点采集动态模拟信号,进而对模拟信号进行了频域分析和时-频分析,相对于时域分析,可以更有效地掌握尾流场中不同能量尺度涡结构的时空变化规律,通过与实验结果比较分析,有助于寻找实验信号中的有用部分,对边界层分离、旋涡脱落等复杂流动现象可以更为直观地分析研究。
The disturbance noise is always existence in data acquisition, which would be confused with the usable signal and influence the analysis and the research. We propose the pretreatment of the signal before the time-frequency analysis and frequency analysis in this paper. Over the applications of the EMD-based, we reduced the noise by self-adapted filtering. Compared with the wavelet packets, the EMD-based method has more accurate analysis in local region. The tradition signal processing method would also lose the usable signal in the same frequency region when removing the disturbing signal. We propose to remove the disturbing signal in the energy characteristic scale, which could keep the usable signal. Because of the existence of the different energy-scale in the flow distribution, we also propose to polish the large-scale eddies. Since the EMD method proposes the signal based on the self-characteristic-scale of the signal, we polish eddies in the EMD method, which could help us to analyze the movement regular of the large eddies.
The experiment is an important method to research the circular cylinders. In order to find more valuable information to reveal the mechanism of the flow, we process the gas-solid synchronization signals by time-frequency analysis and frequency analysis method. We also analyze and describe the regular of eddies changing in the flow distribution from the energy characteristic scale.
The tradition numerical simulation researches the circular cylinders from the time analysis, which could show us the directly phenomenon. In this paper, we advanced the three-dimensional numerical simulation, based on the LES method of Fluent. We measured the gas fluctuating velocity and the solid fluctuating pressure by means of setting up the surface point. The simulation data would be also processed by time-frequency analysis and frequency analysis method. By comparing the experimental result and the simulation result, we could find the flow regular in different region, pick up the usable signal and grasp the regular of eddies changing.
引文
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[4]Braun S,Feldman M.Time-frequency characteristics of non-linear systems[J],Mechanical Systems and Singal Processing,1997,11(4):611-620
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[20]S.Mallat.A theory for multi-resolution signal decomposition the wavelet representation.IEEE Trans.On Pattern Analysis and Machine Intell.1989,11(7):674-693
[21]J.Patrick,Lough Lin,Leon Cohen.The uncertainty principle:Global,Local,or Both.IEEE Transactions Signal Processing.2004,52(5):1218-1227
[22]张丹,吴瑛。STFT在跳频信号分析中的应用。现代电子技术,2005,28(10):60-61
[23]Ville J.Theorie et applications de la notion de signal analytique[J].Cables et transmission,1948,2A:61-94
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[28]邹红星,周小波,李衍达。时-频分析:回溯与前瞻[J]。电子学报,2000,28(9):78-84
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[33]行鸿彦,刘照泉,万明习。基于小波变换的广义相关时延估计算法[J]。2002,27(1):88-93
[34]Huang N E.Shen Z.Long S R,et al.The Empirical Mode Decomposition and the Hilbert Spectrum for Nonlinear and Non-stationary Time Series Analysis,Proc.R..Soc.London.A,1998.454:903-995
[35]Farge M.Schneider K.Analysis and Computing Turbulent Flows Using Wavelets:New trends in turbulence Turbulence:aspects nouveaux M.LESIERU,A.Yaglom,E David Eds.Spring,2001,450-503
[36]Huang N E.Shen Z.Long S R,et al.A new view of nonlinear water waves:the Hilbert spectrum[J].Annual Review of Fluid Mechanics,1999,31:417-457
[37]公茂盛,谢礼立。HHT方法在地震工程中的应用之初步探讨。世界地震工程。2003,19(3),39-43
[38]张义平,李夕兵。基于HHT方法的爆破地震信号分析。工程爆破。2005,11(1),1-7
[39]杜寿吕,梁虹。基于Hilbert-Huang变换的第一心音信号时一频分析。云南民族大学学报。2004,13(2),95-98
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