Distribution Modal Identification based on Radom Decrement Technique

PDF(891 KB)

Journal of Vibration and Shock ›› 2017, Vol. 36 ›› Issue (17) : 48-54.

LU Jingzhou1, Sung Han Sim2, Billie F. Spencer, Jr.3

Author information +

History +

Abstract

Technology for decentralized processing and parallel analysis is essential to realize a dense array of wireless smart sensors networks on large-scale civil structures. This paper presents a decentralized data aggregation approach for system identification based on the random decrement technique (RDT). The performance of RDT–based decentralized data aggregation is experimentally investigated using a two side simply supported plate model. Using ISM400 wireless smart sensors, the random decrement function are obtained from the measured acceleration time histories of the plate by adopting natural excitation technique (NExT). A time domain algorithms integrating NExT and eigensystem realization algorithm (ERA), combined with the method of stability diagram (SD) to eliminate the false mode, was applied to identify modal parameters of the plate. The identification result was compared with that based on the centralized method. The global mode shapes are close to those from centralized method according to modal assurance criterion (MAC).

Key words

random decrement technique (RDT) / distributed sensor networks / eigensystem realization algorithm ( ERA) / stabilization diagram (SD) / modal identification

Cite this article

EndNote

Ris (Procite)

Bibtex

Download Citations

LU Jingzhou1, Sung Han Sim2, Billie F. Spencer, Jr.3. Distribution Modal Identification based on Radom Decrement Technique[J]. Journal of Vibration and Shock, 2017, 36(17): 48-54

References

[1] Sung-Han Sim and B F Spencer Jr. Decentralized strategies for monitoring structures using wireless smart sensor networks[R]. NSEL Report Series, No. 019, University of Illinois at Urbana-Champaign, U.S.A., 2010.
[2] Nagayama T and Spencer B F Jr. Structural health monitoring using smart sensors[R]. NSEL Report Series, No. 001 , University of Illinois at Urbana-Champaign, U.S.A., 2007.
[3] 刘宇飞，辛克贵，樊健生，崔定宇. 环境激励下结构模态参数识别方法综述[J].工程力学，2014，31（4）：46-53.
Liu Yufei, Xin Kegui, Fan Jiansheng, Cui Dingyu. A review of structure modal identification methods through ambient excitation[J]. Engineering Mechanics, 214,31(4):46-53.
[4] Peeters B and De Roeck G. Reference-based stochastic subspace identification in civil engineering[J]. Inverse Problems in Engineering, 2000, 8: 47-7.
[5] 张敏，谢慧才，Sung Han Sim , B F Spencer Jr. 基于随机子空间的分布式结构模态参数识别[J].深圳大学学报，2009，26（4）：394-399.
Zhang Min, Xie Huicai, Sung-Han Sim BF Spencer Jr. Distribution modal identification based on stochastic subspace method[J]. Journal of Shenzhen University Science and Engineering. 2009,26(4):394-399.
[6] 张敏，谢慧才，Sung Han Sim , B F Spencer Jr. 基于分布式传感网络的结构模态识别方法[J].土木工程学报，2010，43（3）：106-110.
Zhang Min, Xie Huicai, Sung-Han Sim BF Spencer Jr. Modal identification technique based on distributed sensor networks[J]. China Civil Engieering Journal. 2010,43(3):106-110.
[7] Cole H A． On-the-line analysis of random vibration[C]. AIAA / ASME 9th Structure, Structural Dynamics and Materials Conference, AIAA paper, 1968:268-288.
[8] Cole H A． Method and apparatus for measuring the damping characteristic of a structure[P]. United State Patent, No:3620069,1971.
[9] 陈德成，姜节胜．随机减量技术的方法与理论[J]．振动与冲击，1984，3(4) :31-39.
Chen Decheng, Jiang Jiesheng. Method and Theory of Random Decrement Technique[J]. Journal of Vibration and Shock, 1984,3(4):31-39.
[10] 刘剑锋，李元兵，张启伟. 基于改进随机减量法和小波变换的结构模态参数识别[J]. 同济大学学报，2015，43（10）：1447-1453.
Liu Jianfeng, Li Yuanbing， Zhang Qiwei. Identification for modal parameters based on improved random decrement technique and wavelet transform[J]. Journal of Tongji University, 2015,43(10):1447-1453.
[11] 罗钧，刘纲，黄宗明. 基于随机减量法的非平稳激励下模态参数识别[J]. 振动与冲击，2015，34（21）：19-24.
Luo Jun, Liu Gang, Huang Zongming. Modal parametric identification under non-stationary excitation based on random decrement method[J]. Journal of vibration and shock, 2015,34(21):19-24.
[12] Sung Han Sim, Juan Francisco Carbonell-Marquez, B.F. Spencer Jr, etal. Decentralized random decrement technique for efficient data aggregation and system identification in wireless smart sensor networks[J]. Probabilistic Engineering Mechanics, 2011,26:81-91.
[13] 黄方林，何旭辉，陈政清等.随机减量法在斜拉桥拉索模态参数识别中的应用[J].机械强度，2002，，24（3）:331-334.
Huang Fanglin, He Xuhui, Chen Zhengqing, et al. Application of random decrement technique to modal parameter identification of cables for a cable-stayed bridge[J]. Journal of Mechanical Strength. 2002,24(3):331-334.
[14] Vandiver J K，Dunwoody A B，Campbell R B，et al． A mathematical basis for the random decrement vibration signature analysis technique[J]． Transactions of the ASME Journal of Mechanical Design，1982，104: 307-313.
[15] Brincker R，Krenk S，Kirkegaard P H，et al． Identification of dynamical properties from correlation function estimates[J]．Bygningsstatiske Meddelllser，1992，63( 1) : 1-38.
[16] Asmussen JC. Modal analysis based on the random decrement technique application to civil engineering structures[D]. Ph.D. thesis. Denmark: University of Aalborg; 1997.
[17] Juan J N, Pappa R S. An elgensystem realization algorithm (ERA) for modal parameter identification and model reduction [J]. Journal of Guidance Control and Dynamics, 1985, 8 (5): 620-627.