Detail publikace

Damage Identification Using Artificial Neural Network-Aided Aimed Multilevel Sampling Method

ŠPLÍCHAL, B. LEHKÝ, D

Originální název

Damage Identification Using Artificial Neural Network-Aided Aimed Multilevel Sampling Method

Typ

článek v časopise - ostatní, Jost

Jazyk

angličtina

Originální abstrakt

Structural health monitoring is extremely important for sustaining and preserving the service life of civil structures. Research to identify the damage can detect, locate, quantify and, where appropriate, predict potential structural damage. This paper is about damage identified by non-destructive vibrationbased experiments, which uses the difference between modal frequencies and deflection of an initial and damaged structure. The main objective of this paper is to present a hybrid method for structural damage identification combining artificial neural network and aimed multilevel sampling method. The combination of these approaches yields a more efficient damage identification in terms of time and accuracy of damage localization and damage extent determination

Klíčová slova

Damage identification, artificial neural network, aimed multilevel sampling, inverse analysis.

Autoři

ŠPLÍCHAL, B.; LEHKÝ, D

Vydáno

31. 12. 2023

Nakladatel

VSB-Technical University of Ostrava

Místo

Ostrava

ISSN

1804-4824

Periodikum

Transactions of the VŠB – Technical University of Ostrava, Civil Engineering Series

Ročník

23

Číslo

2

Stát

Česká republika

Strany od

61

Strany do

66

Strany počet

6

URL

http://tces.vsb.cz

BibTex

@article{BUT185580,
  author="Bohumil {Šplíchal} and David {Lehký}",
  title="Damage Identification Using Artificial Neural Network-Aided Aimed Multilevel Sampling Method",
  journal="Transactions of the VŠB – Technical University of Ostrava, Civil Engineering Series",
  year="2023",
  volume="23",
  number="2",
  pages="61--66",
  doi="10.35181/tces-2023-0017",
  issn="1804-4824",
  url="http://tces.vsb.cz"
}