Experimental and numerical studies on model updating method of damage severity identification utilizing four cost functions

被引:45
作者
An, Yonghui [1 ]
Ou, Jinping [1 ]
机构
[1] Dalian Univ Technol, Sch Civil Engn, Dalian 116024, Peoples R China
关键词
damage severity identification; damage detection; correlation coefficient; assurance criterion; health monitoring; steel-truss bridge; EIGENSYSTEM REALIZATION-ALGORITHM; NATURAL EXCITATION TECHNIQUE; INDEXES;
D O I
10.1002/stc.480
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
As the final stage of damage identification, damage severity identification has great significance to structural safety assessment and decision-making in maintenance. Take the damage detection of truss structures for instance; the stochastic damage locating vector method has great advantages. However, the method is a localization technique designed to provide information in damage location only. Many present damage severity identification methods suffer from great error due to high noise. Therefore, it is imperative to develop a new identification method for truss structural health monitoring. To solve this problem, this paper presents the model updating method of damage severity identification based on four cost functions: (i) correlation coefficient of free vibration accelerations; (ii) correlation coefficient of local mode shapes; (iii) free vibration accelerations assurance criterion; and (iv) local modal assurance criterion. In these functions, correlation coefficient and correlation degree of free vibration accelerations of measured nodes are first proposed to identify damage severity. Moreover, a simple supported bailey steel-truss bridge Benchmark Model has been designed and constructed. The span is 8?m with the scaled ratio 1:25. Based on the model, both experimental and numerical simulation results using these procedures under pulse excitation indicate that they are feasible and effective. In addition, the proposed techniques exhibit high-noise insusceptibility. Copyright (c) 2011 John Wiley & Sons, Ltd.
引用
收藏
页码:107 / 120
页数:14
相关论文
共 26 条
[1]  
An YH, 2010, 5 WORLD C STRUCT CON
[2]  
An YH, 2010, P INT S LIF CYCL PER, P189
[3]  
[Anonymous], 1982, P 1 INT MOD AN C ORL
[4]   Structure Damage Detection Using Neural Network with Multi-Stage Substructuring [J].
Bakhary, Norhisham ;
Hao, Hong ;
Deeks, Andrew J. .
ADVANCES IN STRUCTURAL ENGINEERING, 2010, 13 (01) :95-110
[5]   Load vectors for damage localization [J].
Bernal, D .
JOURNAL OF ENGINEERING MECHANICS-ASCE, 2002, 128 (01) :7-14
[6]   Flexibility-based damage localization from stochastic realization results [J].
Bernal, Dionisio .
JOURNAL OF ENGINEERING MECHANICS, 2006, 132 (06) :651-658
[7]   Natural excitation technique and eigensystem realization algorithm for phase I of the IASC-ASCE benchmark problem: Simulated data [J].
Caicedo, JM ;
Dyke, SJ ;
Johnson, EA .
JOURNAL OF ENGINEERING MECHANICS, 2004, 130 (01) :49-60
[8]   Novel Laplacian scheme and multiresolution modal curvatures for structural damage identification [J].
Cao, Maosen ;
Qiao, Pizhong .
MECHANICAL SYSTEMS AND SIGNAL PROCESSING, 2009, 23 (04) :1223-1242
[9]   Structural damage detection using decentralized controller design method [J].
Chen, Bilei ;
Nagarajaiah, Satish .
SMART STRUCTURES AND SYSTEMS, 2008, 4 (06) :779-794
[10]   Experimental verification of the flexibility-based damage locating vector method [J].
Gao, Y. ;
Spencer, B. F., Jr. ;
Bernal, D. .
JOURNAL OF ENGINEERING MECHANICS, 2007, 133 (10) :1043-1049