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

Bohumil Splichal, David Lehky
Transactions of the VSB - Technical University of Ostrava, Civil Engineering Series
2023, Volume 23, Issue 2, Pages 61-66
Doi: 10.35181/tces-2023-0017
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 vibration-based 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.
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