Structural damage detection by using genetic algorithms: a comparison of different types of individual coding
Abstract
Abstract
In this paper, genetic algorithms are used to solve the structural damage
detection problem. Three types of representation of individuals are com- pared: binary, real and binary with redundant representation. The binary
and real-coded algorithms compute the damage extension for each element
in the structure, therefore, a re-starting process of individuals is used. The
redundant representation algorithm searches the damaged elements in a
dynamic way and quantifes the damage for these elements only. A truss
structure under different damage scenarios
is analyzed, being damage
considered a reduction in the elasticity module of the damaged element.
Results show that the redundant representation algorithm presents the
best option to locate and quantify damage in a structure.
detection problem. Three types of representation of individuals are com- pared: binary, real and binary with redundant representation. The binary
and real-coded algorithms compute the damage extension for each element
in the structure, therefore, a re-starting process of individuals is used. The
redundant representation algorithm searches the damaged elements in a
dynamic way and quantifes the damage for these elements only. A truss
structure under different damage scenarios
is analyzed, being damage
considered a reduction in the elasticity module of the damaged element.
Results show that the redundant representation algorithm presents the
best option to locate and quantify damage in a structure.
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How to Cite
[1]
“Structural damage detection by using genetic algorithms: a comparison of different types of individual coding”, Ing. y Des., vol. 27, no. 27, pp. 169–186, Sep. 2010, Accessed: Oct. 23, 2026. Available: https://rcientificas.uninorte.edu.co/ingenieria/article/view/873




