Spurious mode distinguish by eigensystem realization algorithm with improved stabilization diagram

被引:26
作者
Qu, Chun-Xu [1 ,2 ]
Yi, Ting-Hua [1 ]
Yang, Xiao-Mei [1 ]
Li, Hong-Nan [1 ]
机构
[1] Dalian Univ Technol, Sch Civil Engn, Dalian 116024, Peoples R China
[2] State Key Lab Bldg Safety & Built Environm, Beijing 100013, Peoples R China
基金
中国国家自然科学基金;
关键词
eigensystem realization algorithm (ERA); spurious mode; stabilization diagram; Hankel matrix; singular value decomposition (SVD); FUNDAMENTAL 2-STAGE FORMULATION; BAYESIAN SYSTEM-IDENTIFICATION;
D O I
10.12989/sem.2017.63.6.743
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Modal parameter identification plays a key role in the structural health monitoring (SHM) for civil engineering. Eigensystem realization algorithm (ERA) is one of the most popular identification methods. However, the complex environment around civil structures can introduce the noises into the measurement from SHM system. The spurious modes would be generated due to the noises during ERA process, which are usually ignored and be recognized as physical modes. This paper proposes an improved stabilization diagram method in ERA to distinguish the spurious modes. First, it is proved that the ERA can be performed by any two Hankel matrices with one time step shift. The effect of noises on the eigenvalues of structure is illustrated when the choice of two Hankel matrices with one time step shift is different. Then, a moving data diagram is proposed to combine the traditional stabilization diagram to form the improved stabilization diagram method. The moving data diagram shows the mode variation along the different choice of Hankel matrices, which indicates whether the mode is spurious or not. The traditional stabilization diagram helps to determine the concerned truncated order before moving data diagram is implemented. Finally, the proposed method is proved through a numerical example. The results show that the proposed method can distinguish the spurious modes.
引用
收藏
页码:743 / 750
页数:8
相关论文
共 19 条
  • [1] [Anonymous], 2012, Smart Mater. Struct, DOI [DOI 10.1088/0964-1726/21/12/125023, DOI 10.1088/0964-1726/21/10/105033]
  • [2] Fundamental two-stage formulation for Bayesian system identification, Part I: General theory
    Au, Siu-Kui
    Zhang, Feng-Liang
    [J]. MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2016, 66-67 : 31 - 42
  • [3] Eigensystem realization algorithm (ERA):: reformulation and system pole perturbation analysis
    Bazán, FSV
    [J]. JOURNAL OF SOUND AND VIBRATION, 2004, 274 (1-2) : 433 - 444
  • [4] An approach to operational modal analysis using the expectation maximization algorithm
    Cara, F. Javier
    Carpio, Jaime
    Juan, Jesus
    Alarcon, Enrique
    [J]. MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2012, 31 : 109 - 129
  • [5] Regularised finite element model updating using measured incomplete modal data
    Chen, Hua-Peng
    Maung, Than Soe
    [J]. JOURNAL OF SOUND AND VIBRATION, 2014, 333 (21) : 5566 - 5582
  • [6] Ibraham SR, 2001, P 19 IMAC ORL FL
  • [7] JAMES GH, 1995, MODAL ANAL, V10, P260
  • [8] Jeffrey B.B., 1998, LINEAR OPTIMAL CONTR
  • [9] AN EIGENSYSTEM REALIZATION-ALGORITHM FOR MODAL PARAMETER-IDENTIFICATION AND MODEL-REDUCTION
    JUANG, JN
    PAPPA, RS
    [J]. JOURNAL OF GUIDANCE CONTROL AND DYNAMICS, 1985, 8 (05) : 620 - 627
  • [10] Lei Y, 2014, STRUCT STAB DYN, V14