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Damage identification using combined transient power flow balance and acceleration matching technique
Author(s) -
Varghese Cibu K.,
Shankar Krishnapillai K.
Publication year - 2014
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.1551
Subject(s) - acceleration , control theory (sociology) , noise (video) , particle swarm optimization , power (physics) , cantilever , weighting , structural engineering , mathematics , engineering , computer science , algorithm , physics , acoustics , control (management) , classical mechanics , quantum mechanics , artificial intelligence , image (mathematics)
This paper presents a multiobjective optimization formulation to detect and quantify crack damage in beam structures at variable locations. It is implemented at the substructure level where the concept is to balance the instantaneous power flow by equating the input power to the dissipated power and the time rate of change of kinetic and strain energies and power transferred to adjacent substructures. This imbalance is reduced to zero to identify the structural parameters or damages. For improved results, the power balance method is combined with conventional acceleration matching method where the objective is to minimize the deviation between measured and estimated accelerations—no additional sensors are required to incorporate the extra power flow balance criteria. Numerical simulations are performed for a lumped mass system, a planar truss structure, and a cantilever beam of 20 elements with multiple damages to evaluate the accuracy of the proposed method. Effects of noise are also taken into account by contaminating the measured responses with 3%, 5%, and 10% Gaussian noise. The particle swarm optimization is used as the optimization algorithm, and normalized fitness functions are defined for both power flow and acceleration components with weighted aggregation multiobjective optimization technique. The effects of various weighting factors for the combined objective function are also studied. The results demonstrate that improvement in accuracy of damage detection is achieved by the combined method, when compared with previous acceleration only matching method as well as other methods. Copyright © 2013 John Wiley & Sons, Ltd.