High-sensitivity damage detection based on enhanced nonlinear dynamics

被引:20
作者
Epureanu, BI [1 ]
Yin, SH
Derriso, MM
机构
[1] Univ Michigan, Dept Mech Engn, Ann Arbor, MI 48109 USA
[2] VASM, AFRL, Struct Hlth Monitoring, Wright Patterson AFB, OH 45433 USA
关键词
D O I
10.1088/0964-1726/14/2/004
中图分类号
TH7 [仪器、仪表];
学科分类号
0804 ; 080401 ; 081102 ;
摘要
One of the most important aspects of detecting damage in the framework of structural health monitoring is increasing the sensitivity of the monitored feature to the presence, location, and extent of damage. Distinct from previous techniques of obtaining information about the monitored structure-such as measuring frequency response functions-the approach proposed herein is based on an active interrogation of the system. This interrogation approach allows for the embedding of the monitored system within a larger system by means of a nonlinear feedback excitation. The dynamics of the larger system is then analyzed in state space, and the shape of the attractor of its dynamics is used as a complex geometric feature which is very sensitive to damage. The proposed approach is implemented for monitoring the structural integrity of a panel forced by transverse loads and undergoing limit cycle oscillations and chaos. The nonlinear von Karman plate theory is used to obtain a model for the panel combined with a nonlinear feedback excitation. The presence of damage is modeled as loss of stiffness of various levels in a portion of the plate at various locations. The sensitivity of the proposed approach to parametric changes is shown to be an effective tool in detecting damages.
引用
收藏
页码:321 / 327
页数:7
相关论文
共 30 条
[1]   Enhanced structural damage detection using alternating projection methods [J].
Abdalla, MO ;
Grigoriadis, KM ;
Zimmerman, DC .
AIAA JOURNAL, 1998, 36 (07) :1305-1311
[2]  
AGBABIAN MS, 1990, ASCE J ENG MECH, V117, P370
[3]   Structural integrity monitoring of composite patch repairs using wavelet analysis and neural networks [J].
Amaravadi, VK ;
Mitchell, K ;
Rao, V ;
Derriso, MM .
SMART STRUCTURES AND MATERIALS 2002: SMART STRUCTURES AND INTEGRATED SYSTEMS, 2002, 4701 :156-166
[4]  
[Anonymous], 1996, LA13070MS
[5]   On model updating using neural networks [J].
Atalla, MJ ;
Inman, DJ .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 1998, 12 (01) :135-161
[6]   Optimal tracking of parameter drift in a chaotic system: Experiment and theory [J].
Chatterjee, A ;
Cusumano, JP ;
Chelidze, D .
JOURNAL OF SOUND AND VIBRATION, 2002, 250 (05) :877-901
[7]   Exploiting chaotic dynamics for detecting parametric variations in aeroelastic systems [J].
Epureanu, BI ;
Tang, LS ;
Païdoussis, MP .
AIAA JOURNAL, 2004, 42 (04) :728-735
[8]   Coherent structures and their influence on the dynamics of aeroelastic panels [J].
Epureanu, BI ;
Tang, LSS ;
Païdoussis, MP .
INTERNATIONAL JOURNAL OF NON-LINEAR MECHANICS, 2004, 39 (06) :977-991
[9]   Vibration-based structural damage identification [J].
Farrar, CR ;
Doebling, SW ;
Nix, DA .
PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY OF LONDON SERIES A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES, 2001, 359 (1778) :131-149
[10]   STRUCTURAL-SYSTEM IDENTIFICATION .1. THEORY [J].
GHANEM, R ;
SHINOZUKA, M .
JOURNAL OF ENGINEERING MECHANICS, 1995, 121 (02) :255-264