Solid Mechanics and Vehicle Conceptual Design

Multi-degree-of-freedom non-Gaussian random vibration control

  • MENG Han ,
  • HUANG Hai ,
  • HUANG Zhou
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  • 1. School of Astronautics, Beihang University, Beijing 100083, China;
    2. Institute of Systems Engineering, China Academy of Engineering Physics, Mianyang 621900, China

Received date: 2016-05-20

  Revised date: 2016-09-07

  Online published: 2016-10-09

Abstract

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 pseudo-random 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 ±3 dB 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.

Cite this article

MENG Han , HUANG Hai , HUANG Zhou . Multi-degree-of-freedom non-Gaussian random vibration control[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2017 , 38(2) : 220458 -220465 . DOI: 10.7527/S1000-6893.2016.0253

References

[1] 陈章位, 于慧君. 振动控制技术现状与进展[J]. 振动与冲击, 2009, 28(3):73-77. CHEN Z W, YU H J. Existing state and development of vibration control technology[J]. Journal of Vibration and Shock, 2009, 28(3):73-77(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 multi-input 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).

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