Open AccessDamage recognition based on Generalized Genetic Algorithm
Author(s) -
Huaxin Zhang
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1676/1/012223
Subject(s) - genetic algorithm , modal , convergence (economics) , identification (biology) , algorithm , transformation (genetics) , computer science , mutation , residual , mathematical optimization , finite element method , mathematics , engineering , structural engineering , biochemistry , chemistry , botany , gene , polymer chemistry , economics , biology , economic growth
A new optimization approach to solving problems concerning structural damage identification with finite element model is introduced. In this approach, the generalized genetic algorithm is applied to damage recognition with its advantage of directed evolution and two-phase transformation. To employ the method, objective function is constructed by the residual of modal frequency and incomplete modal mode. Meanwhile the recombination and mutation operators are also improved with sparsity constrain. The results show that modified generalized genetic algorithm performs better in convergence speed and accuracy than traditional optimization approach in damage identification.