Multi Input Multi Output (MIMO) random vibration test is of utter importance in product validation. As a type of time domain method, inverse system methods are capable of generating drive signals directly from reference ones (i.e., the desired response signals). However, in practice, these methods are prone to produce unstable results. To address this issue, an inverse multi-step prediction model is induced from the finite difference model of the system, and a MIMO random vibration test control scheme utilizing both the inverse multi-step prediction model and matrix power algorithm are proposed. First, a simulation of double-input-double-output-random-vibration test on a cantilever beam is conducted to show that the inverse multi-step prediction model can generate drive signals needed to satisfy the control requirement. After that, the capability of the proposed MIMO random vibration test control scheme is further validated in a test performed on a three-axis shaker.
[1] 邹学锋, 郭定文, 潘凯, 等. 综合载荷环境下高超声速飞行器结构多场联合强度试验技术[J]. 航空学报, 2018, 39(12):222326. ZOU X F, GUO D W, PAN K, et al. Test technique for multi-load combined strength of hypersonic vehicle structure under complex loading environment[J]. Acta Aeronautica et Astronautica Sinica, 2018, 39(12):222326(in Chinese).
[2] CUI X, CHEN H, HE X, et al. Matrix power control algorithm for multi-input multi-output random vibration test[J]. Chinese Journal of Aeronautics, 2011, 24(6):741-748.
[3] CUI S, CHEN H, HE X, et al. Multi-input multi-output random vibration control using Tikhonov filter[J]. Chinese Journal of Aeronautics, 2016, 29(6):1649-1663.
[4] 张步云, 汪若尘, 曾发林. MIMO随机加正弦振动试验J-阻抗复合控制算法[J]. 振动.测试与诊断, 2017, 37(6):1089-1093,1274. ZHANG B Y, WANG R C, ZENG F L. J-impedance compound control algorithm for MIMO random plus sinusoidal vibration test[J]. Journal of Vibration, Measurement & Diagnosis, 2017, 37(6):1089-1093,1274(in Chinese).
[5] ZHENG R, CHEN H, HE X. Control method for multi-input multi-output non-Gaussian random vibration test with cross spectra consideration[J]. Chinese Journal of Aeronautics, 2017, 30(6):1895-1906.
[6] CUI S, CHEN H, HE X. Time-domain approach for multi-exciter random environment test[J]. Journal of Sound and Vibration, 2017, 398:52-69.
[7] CUI S, CHEN H, HE X, et al. Control algorithm update for multi-input multi-output random environment test[J]. Mechanical Systems and Signal Processing, 2018, 111:643-662.
[8] 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. Generation of 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).
[9] KAMMER D C. Input force reconstruction using a time domain technique[J]. Journal of Vibration and Acoustics, 1998, 120(4):868-874.
[10] STELTZNER A D, KAMMER D C. Input force estimation using an inverse structural filter[C]//Proceedings of the 17th International Modal Analysis Conference. Kissimmee, Florida:Society for Experimental Mechanics, 1999:954-960.
[11] ALLEN M, CARNE T. Comparison of Inverse Structural Filter (ISF) and Sum of Weighted Accelerations Time (SWAT) domain force identification methods[C]//47th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference. Reston, VA:AIAA, 2006.
[12] ALLEN M S, CARNE T G. Delayed, multi-step inverse structural filter for robust force identification[J]. Mechanical Systems and Signal Processing, 2008, 22(5):1036-1054.
[13] ZHENG R, CHEN H, HE X, et al. Probability distributions control for multi-input multi-output stationary non-Gaussian random vibration test[J]. Journal of Vibration and Control, 2017, 24(21):5201-5210.
[14] ZHENG R, CHEN H, HE X. Control method for multiple-input multiple-output non-gaussian random vibration test[J]. Packaging Technology and Science, 2017, 30(7):331-345.
[15] 廖林雨. 结构振动的逆系统预测控制[D]. 武汉:华中科技大学, 2011:9-17. LIAO L Y. Inverse system predictive control of structural vibration[D]. Wuhan:Huazhong University of Science and Technology, 2011:9-17(in Chinese).
[16] 朱锐, 杭晓晨, 姜东, 等. 基于奇异值分解的ERA改进算法及模态定阶[J]. 振动.测试与诊断, 2018, 38(1):115-122. ZHU R, HANG X C, JIANG D, et al. Improved ERA algorithm and modal order determination based on SVD[J]. Journal of Vibration, Measurement and Diagnosis, 2018, 38(1):115-122(in Chinese).
[17] 蒲黔辉, 洪彧, 王高新, 等. 快速特征系统实现算法用于环境激励下的结构模态参数识别[J]. 振动与冲击, 2018, 37(6):55-60. PU Q H,HONG Y,WANG G X, et al. Fast eigensystem realization algorithm based structural modal parameters identification for ambient tests[J]. Journal of Vibration and Shock, 2018, 37(6):55-60(in Chinese).
[18] JUANG J N, PHAN M. Identification and control of mechanical systems[M]. Cambridge:Cambridge University Press, 2001:256-272.
[19] HANSEN P C. The truncated SVD as a method for regularization[J]. Bit Numerical Mathematics, 1987, 27(4):534-553.
[20] 吴太旗, 邓凯亮, 黄谟涛, 等. 一种改进的不适定问题奇异值分解法[J]. 武汉大学学报(信息科学版), 2011, 36(08):900-903,880. WU T Q, DENG K L, HUANG M T, et al. An improved singular values decomposition method for ill-posed problem[J]. Geomatics and Information Science of Wuhan University, 2011, 36(08):900-903,880(in Chinese).
[21] SMALLWOOD D O, PAEZ T L. A frequency domain method for the generation of partially coherent normal stationary time domain signals[J]. Shock and Vibration, 1991, 1(1):45-53.
CJA