AE source location by neural networks with arrival time profiles

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61388998%3A_____%2F09%3A00334346" target="_blank" >RIV/61388998:_____/09:00334346 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

AE source location by neural networks with arrival time profiles

Popis výsledku v původním jazyce

Correct localization of acoustic emission (AE) sources is a basic requirement in AE analysis and consequent evaluation of damage mechanism. The localization procedures using artificial neural networks (ANN) represent today highly effective, alternative approach to classical triangulation algorithms. Nevertheless, their application possibilities are limited due to problematic collecting of sufficiently extensive training and testing data sets together with the non-portability of particular trained network to any other object. A new ANN-based approach, using so-called signal arrival time profiles, is proposed to overcome both limitations. Such approach provides the ANN training on numerical models and allows the application of learned ANN on real structures of various scales and materials. This enables considerable extension of ANN application possibilities. New method is illustrated on experimental data obtained during pen-tests on a steel plate, and its remarkable advantages are discus

Název v anglickém jazyce

AE source location by neural networks with arrival time profiles

Popis výsledku anglicky

Correct localization of acoustic emission (AE) sources is a basic requirement in AE analysis and consequent evaluation of damage mechanism. The localization procedures using artificial neural networks (ANN) represent today highly effective, alternative approach to classical triangulation algorithms. Nevertheless, their application possibilities are limited due to problematic collecting of sufficiently extensive training and testing data sets together with the non-portability of particular trained network to any other object. A new ANN-based approach, using so-called signal arrival time profiles, is proposed to overcome both limitations. Such approach provides the ANN training on numerical models and allows the application of learned ANN on real structures of various scales and materials. This enables considerable extension of ANN application possibilities. New method is illustrated on experimental data obtained during pen-tests on a steel plate, and its remarkable advantages are discus

Druh

D - Stať ve sborníku

CEP obor

BI - Akustika a kmity

OECD FORD obor

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Projekt

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

Návaznosti

Z - Vyzkumny zamer (s odkazem do CEZ)

Rok uplatnění

2009

Kód důvěrnosti údajů

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

Název statě ve sborníku

NDT in PROGRESS

ISBN

978-80-214-3968-9

ISSN

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e-ISSN

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Počet stran výsledku

8

Strana od-do

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Název nakladatele

University of Technology Brno

Místo vydání

Brno

Místo konání akce

Praha

Datum konání akce

12. 10. 2009

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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