Damage Identification Using Artificial Neural Network-Aided Aimed Multilevel Sampling Method
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26110%2F23%3APU149726" target="_blank" >RIV/00216305:26110/23:PU149726 - isvavai.cz</a>
Result on the web
<a href="http://tces.vsb.cz" target="_blank" >http://tces.vsb.cz</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.35181/tces-2023-0017" target="_blank" >10.35181/tces-2023-0017</a>
Alternative languages
Result language
angličtina
Original language name
Damage Identification Using Artificial Neural Network-Aided Aimed Multilevel Sampling Method
Original language description
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
Czech name
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Czech description
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Classification
Type
J<sub>ost</sub> - Miscellaneous article in a specialist periodical
CEP classification
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OECD FORD branch
20101 - Civil engineering
Result continuities
Project
<a href="/en/project/TM04000012" target="_blank" >TM04000012: A concrete bridge health interpretation system based on mutual boost of big data and physical mechanism</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Transactions of the VŠB – Technical University of Ostrava, Civil Engineering Series
ISSN
1804-4824
e-ISSN
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Volume of the periodical
23
Issue of the periodical within the volume
2
Country of publishing house
CZ - CZECH REPUBLIC
Number of pages
6
Pages from-to
61-66
UT code for WoS article
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EID of the result in the Scopus database
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