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Detection and classification of structural changes using artificial immune systems and fuzzy clustering

Autor
Anaya, M.; Tibaduiza, D.A.; Pozo, F.
Tipus d'activitat
Article en revista
Revista
International journal of bio-inspired computation
Data de publicació
2017-01-01
Volum
9
Número
1
Pàgina inicial
35
Pàgina final
52
DOI
https://doi.org/10.1504/IJBIC.2017.10002804 Obrir en finestra nova
Repositori
http://hdl.handle.net/2117/104341 Obrir en finestra nova
URL
http://www.inderscience.com/info/inarticle.php?artid=81843 Obrir en finestra nova
Resum
Among all the elements that are integrated into a structural health monitoring (SHM) system, methods or strategies for damage detection and classification are nowadays playing a key role in enhancing the operational reliability of critical structures in several industrial sectors. The main contribution of this paper is the application of a new methodology to detect and classify structural changes. The methodology is based on: 1) an artificial immune system (AIS) and the notion of affinity is use...
Citació
Anaya, M., Tibaduiza, D.A., Pozo, F. Detection and classification of structural changes using artificial immune systems and fuzzy clustering. "International journal of bio-inspired computation", 1 Gener 2017, vol. 9, núm. 1, p. 35-52.
Paraules clau
AIS, PCA, affinity value, artificial immune systems, classification, damage indices, detection, fuzzy clustering, principal component analysis
Grup de recerca
CoDAlab - Control, Modelització, Identificació i Aplicacions

Participants