Multiresponse parameter estimation for finite-element model updating using nondestructive test data

被引:25
|
作者
Bell, Erin Santini [1 ]
Sanayei, Masoud
Javdekar, Chitra N.
Slavsky, Eugene
机构
[1] Univ New Hampshire, Dept Civil Engn, Durham, NH 03824 USA
[2] Tufts Univ, Dept Civil & Environm Engn, Medford, MA 02155 USA
[3] MassBay Community Coll, Dept Mech Engn, Wellesley, MA 02481 USA
[4] Ammann & Whitney Inc, Boston, MA 02108 USA
来源
JOURNAL OF STRUCTURAL ENGINEERING-ASCE | 2007年 / 133卷 / 08期
关键词
parameters; estimation; finite element method; nondestructive tests; structural reliability; monitoring; measurement;
D O I
10.1061/(ASCE)0733-9445(2007)133:8(1067)
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Structural health monitoring using field measurements has developed into a major research area, responding to an increasing demand for evaluating the integrity of civil engineering structures. Model updating through parameter estimation is a key toot in a successful structural health monitoring program. A method for parameter estimation is developed for simultaneous use of static and modal nondestructive test data called the "multiresponse" parameter estimation. An error function normalization technique is also developed to facilitate effective multiresponse parameter estimation. This normalization technique can mitigate some of the numerical issues encountered during the parameter estimation procedure. However, this technique does not degrade the integrity of the parameter estimation procedure. Multiresponse parameter estimation provides an increased level of flexibility and feasibility of model updating for structural health monitoring. This paper presents full integration of static and modal nondestructive test data using both stiffness-based and mass-based error functions for structural health monitoring. A benchmark laboratory grid model of a bridge deck is utilized to illustrate application of both normalization and multiresponse parameter estimation for updating the stiffness and mass parameters using nondestructive test data.
引用
收藏
页码:1067 / 1079
页数:13
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