多自由度非高斯随机振动控制
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摘要
在振动试验台上进行多自由度(MDOF)随机振动激励时,传统的控制方法生成的驱动信号及试验台的响应信号都是高斯信号。但真实的振动干扰信号多是超高斯的;而相比于高斯激励,亚高斯激励可降低驱动信号的最大幅值。为实现多自由度亚高斯和超高斯振动控制,提出一种多自由度非高斯随机振动控制方法,该方法采用系统辨识解决系统耦合问题,而后通过选择特殊的相位生成非高斯伪随机驱动信号,再经过时域随机化得到真随机非高斯驱动信号。基于Hexapod平台的多自由度微振动试验台的亚高斯和超高斯实验表明,在试验台的响应功率谱(PSD)满足工程中常用的±3dB精度的同时,亚高斯驱动信号的最大幅值相比于高斯驱动信号的最大幅值降低了20%以上;超高斯响应信号的峭度与参考峭度的误差在0.2之内。实验结果验证了所提方法的有效性。
The drive signal and the response signal generated by traditional multi-degree-of-freedom(MDOF)random vibration control method are both Gaussian signal.However,the real vibration interference signal is always super-Gaussian,while sub-Gaussian random excitation is mainly used to reduce the maximum amplitude of the drive signal.To achieve MDOF sub-Gaussian and super-Gaussian vibration control,an MDOF non-Gaussian random vibration control method is proposed,which solve the coupling problem through system identification,and select special phase to generate non-Gaussian pseudorandom drive signal,and then the pseudo-random drive signal is transformed to real random non-Gaussian drive signal through time domain randomization.The sub-Gaussian and super-Gaussian experiments based on a Hexapod-based MDOF micro vibration test bed show that the response power spectral density(PSD)of response signals obtained by the proposed method are limited to±3dB error band of reference PSD.Compared to that in the Gaussian experiment,the drive signal in the sub-Gaussian experiment decreases by more than 20%.In the super-Gaussian experiment,the error between the kurtosis of response signal and the reference value is within 0.2.Effectiveness of the proposed method can be validated by the experiment results.
The drive signal and the response signal generated by traditional multi-degree-of-freedom(MDOF)random vibration control method are both Gaussian signal.However,the real vibration interference signal is always super-Gaussian,while sub-Gaussian random excitation is mainly used to reduce the maximum amplitude of the drive signal.To achieve MDOF sub-Gaussian and super-Gaussian vibration control,an MDOF non-Gaussian random vibration control method is proposed,which solve the coupling problem through system identification,and select special phase to generate non-Gaussian pseudorandom drive signal,and then the pseudo-random drive signal is transformed to real random non-Gaussian drive signal through time domain randomization.The sub-Gaussian and super-Gaussian experiments based on a Hexapod-based MDOF micro vibration test bed show that the response power spectral density(PSD)of response signals obtained by the proposed method are limited to±3dB error band of reference PSD.Compared to that in the Gaussian experiment,the drive signal in the sub-Gaussian experiment decreases by more than 20%.In the super-Gaussian experiment,the error between the kurtosis of response signal and the reference value is within 0.2.Effectiveness of the proposed method can be validated by the experiment results.
引文
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[17]陈怀海,王鹏宇,孙建勇.基于逆系统方法的多输入多输出非高斯驱动信号生成[J].航空学报,2016,37(5):1544-1551.CHEN H H,WANG P Y,SUN J Y.Generating multiinput multi-output non-Gaussian driving signal based on inverse system method[J].Acta Aeronautica et Astronautica Sinica,2016,37(5):1544-1551(in Chinese).
[18]Department of Defense.Test method standard for environmental engineering considerations and laboratory test:MIL-STD-810G(w/CHANGE-1)[S].Washington,D.C.:Department of Defense,2014.
[19]SMALLWOOD D O.Multiple shaker random vibration control—An update[R].Albuquerque,NM:Sandia National Labs,1999.
[20]蒋瑜,陈循,陶俊勇.基于时域随机化的超高斯真随机驱动信号生成技术研究[J].振动工程学报,2005,18(4):491-494.JIANG Y,CHEN X,TAO J Y.Study on the generation of super-Gaussian and true-random drive signals using time domain randomization[J].Journal of Vibration Engineering,2005,18(4):491-494(in Chinese).
[21]黄海,王海强,李伟鹏,等.一种六自由度振动激励系统:CN104865034A[P].2015-08-26.HUANG H,WANG H Q,LI W P,et al.A six degree of freedom vibration excitation system:CN104865034A[P].2015-08-26(in Chinese).
[2]CONNON I W.Comments on kurtosis of military vehicle vibration data[J].Journal of the IES,1991,34(6):38-41.
[3]李锦华,李春祥,申建红.非高斯脉动风压的模拟研究[J].振动与冲击,2009,28(9):5-8.LI J H,LI C X,SHEN J H.Simulation of non-Guassian fluctuating wind pressure[J].Journal of Vibration and Shock,2009,28(9):5-8(in Chinese).
[4]XU F,LI C R,JIANG T M.On the shaker simulation of wind-induced non-Gaussian random vibration[J].Shock and Vibration,2016,2016(6):1-10.
[5]蒋培,张春华,陈循,等.超高斯随机振动环境的疲劳强化机理[J].国防科技大学学报,2004,28(3):99-102.JIANG P,ZHANG C H,CHEN X,et al.Fatigue enhancement mechanism of the super-Gaussian random vibration environment[J].Journal of National University of Defense Technology,2004,28(3):99-102(in Chinese).
[6]VAN BAREN J,VAN BAREN P,JENISON M I.The third dimension of random vibration control:2007.01.2270[R].Warrendale,PA:SAE International,2007.
[7]STEINWOLF A.Shaker random testing with low kurtosis:Review of the methods and application for sigma limiting[J].Shock and Vibration,2010,17(3):219-231.
[8]WINTERSTEIN S R.Nonlinear vibration models for extremes and fatigue[J].Journal of Engineering Mechanics,1988,114(10):1772-1790.
[9]SMALLWOOD D O.Generation of stationary non-Gaussian time histories with a specified cross-spectral density[J].Shock and Vibration,1997,4(5-6):361-377.
[10]SMALLWOOD D O.Generating non-Gaussian vibration for testing purposes[J].Sound and Vibration,2005,39(10):18-23.
[11]HSUEH K D,HAMERNIK R P.A generalized approach to random noise synthesis:Theory and computer simulation[J].The Journal of the Acoustical Society of America,1990,87(3):1207-1217.
[12]STEINWOLF A.Approximation and simulation of probability distributions with a variable kurtosis value[J].Computational Statistics&Data Analysis,1996,21(2):163-180.
[13]STEINWOLF A.Shaker random testing with low kurtosis:Review of the methods and application for sigma limiting[J].Shock and Vibration,2010,17(3):219-231.
[14]STEINWOLF A.Vibration testing by non-Gaussian random excitations with specified kurtosis.Part II:Numerical and experimental results[J].Journal of Testing and Evaluation,2014,42(3):672-686.
[15]蒋瑜,陶俊勇,王得志,等.一种新的非高斯随机振动数值模拟方法[J].振动与冲击,2012,31(19):169-173.JIANG Y,TAO J Y,WANG D Z,et al.A novel approach for the numerical simulation of non-Gaussian random vibration[J].Journal of Vibration and Shock,2012,31(19):169-173(in Chinese).
[16]陈家焱,陈章位,周建川,等.基于泊松过程的超高斯随机振动试验控制技术研究[J].振动与冲击,2012,31(6):19-22.CHEN J Y,CHEN Z W,ZHOU J C,et al.Super-Gaussian random vibration test control technique based on Poisson process[J].Journal of Vibration and Shock,2012,31(6):19-22(in Chinese).
[17]陈怀海,王鹏宇,孙建勇.基于逆系统方法的多输入多输出非高斯驱动信号生成[J].航空学报,2016,37(5):1544-1551.CHEN H H,WANG P Y,SUN J Y.Generating multiinput multi-output non-Gaussian driving signal based on inverse system method[J].Acta Aeronautica et Astronautica Sinica,2016,37(5):1544-1551(in Chinese).
[18]Department of Defense.Test method standard for environmental engineering considerations and laboratory test:MIL-STD-810G(w/CHANGE-1)[S].Washington,D.C.:Department of Defense,2014.
[19]SMALLWOOD D O.Multiple shaker random vibration control—An update[R].Albuquerque,NM:Sandia National Labs,1999.
[20]蒋瑜,陈循,陶俊勇.基于时域随机化的超高斯真随机驱动信号生成技术研究[J].振动工程学报,2005,18(4):491-494.JIANG Y,CHEN X,TAO J Y.Study on the generation of super-Gaussian and true-random drive signals using time domain randomization[J].Journal of Vibration Engineering,2005,18(4):491-494(in Chinese).
[21]黄海,王海强,李伟鹏,等.一种六自由度振动激励系统:CN104865034A[P].2015-08-26.HUANG H,WANG H Q,LI W P,et al.A six degree of freedom vibration excitation system:CN104865034A[P].2015-08-26(in Chinese).