Neural network based damage detection of dynamically loaded structures

Kód výsledku v IS VaVaI

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Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Neural network based damage detection of dynamically loaded structures

Popis výsledku v původním jazyce

The aim of the paper is to describe a methodology of damage detection which is based on artificial neural networks in combination with stochastic analysis. The damage is defined as a stiffness reduction (bending or torsion) in certain part of a structure. The key stone of the method is feed-forward multilayer network. It is impossible to obtain appropriate training set for real structure in usage, therefore stochastic analysis using numerical model is carried out to get training set virtually. Due to possible time demanding nonlinear calculations the effective simulation Latin Hypercube Sampling is used here. The important part of identification process is proper selection of input information. In case of dynamically loaded structures their modal properties seem to be proper input information as those are not dependent on actual loading (traffic, wind, temperature). The methodology verification was carried out using laboratory beam.

Název v anglickém jazyce

Neural network based damage detection of dynamically loaded structures

Popis výsledku anglicky

The aim of the paper is to describe a methodology of damage detection which is based on artificial neural networks in combination with stochastic analysis. The damage is defined as a stiffness reduction (bending or torsion) in certain part of a structure. The key stone of the method is feed-forward multilayer network. It is impossible to obtain appropriate training set for real structure in usage, therefore stochastic analysis using numerical model is carried out to get training set virtually. Due to possible time demanding nonlinear calculations the effective simulation Latin Hypercube Sampling is used here. The important part of identification process is proper selection of input information. In case of dynamically loaded structures their modal properties seem to be proper input information as those are not dependent on actual loading (traffic, wind, temperature). The methodology verification was carried out using laboratory beam.

Druh

D - Stať ve sborníku

CEP obor

JM - Inženýrské stavitelství

OECD FORD obor

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Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2009

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

11th International Conference on Engineering Applications of Neural Networks (EANN 2009)

ISBN

978-3-642-03968-3

ISSN

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e-ISSN

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Počet stran výsledku

10

Strana od-do

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Název nakladatele

Neuveden

Místo vydání

London, UK

Místo konání akce

London

Datum konání akce

27. 8. 2009

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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