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Rank‐revealing QR decomposition applied to damage localization in truss structures
Author(s) -
An Yonghui,
Błachowski Bartłomiej,
Zhong Yue,
Hołobut Paweł,
Ou Jinping
Publication year - 2017
Publication title -
structural control and health monitoring
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.587
H-Index - 62
eISSN - 1545-2263
pISSN - 1545-2255
DOI - 10.1002/stc.1849
Subject(s) - truss , truss bridge , sensitivity (control systems) , flexibility (engineering) , rank (graph theory) , set (abstract data type) , matrix (chemical analysis) , flexibility method , structural engineering , computer science , algorithm , bridge (graph theory) , engineering , mathematical optimization , mathematics , finite element method , materials science , medicine , statistics , combinatorics , electronic engineering , composite material , programming language
Summary The purpose of this work is the development of an efficient and high‐sensitive damage localization technique for truss structures, based on the rank‐revealing QR decomposition (RRQR) of the difference‐of‐flexibility matrix. The method is an enhancement of the existing techniques of damage detection, which rely on the set of so‐called damage locating vector (DLV). The advantages of the RRQR decomposition‐based DLV (RRQR‐DLV) method are its less computational effort and high sensitivity to damage. Compared with the frequently used stochastic DLV (SDLV) method, RRQR‐DLV offers higher sensitivity to damage, which has been validated based on the presented numerical simulation. The effectiveness of the proposed RRQR‐DLV method is also illustrated with the experimental validation based on a laboratory‐scale Bailey truss bridge model. The proposed method works under ambient excitation such as traffic excitation and wind excitation; therefore, it is promising for real‐time damage monitoring of truss structures. Copyright © 2016 John Wiley & Sons, Ltd.