About: Neural network AE source location apart from structure size and material

Facets (new session)
Description
Metadata
Settings
- owl:sameAs
- Inference Rule:

About: Neural network AE source location apart from structure size and material Goto Sponge NotDistinct Permalink

An Entity of Type : http://linked.opendata.cz/ontology/domain/vavai/Vysledek, within Data Space : linked.opendata.cz associated with source document(s)

Attributes	Values
rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
Description	AE localization procedures using artificial neural networks (ANN) represent extremely effective alternative to classical triangulation methods. Nevertheless, their application always requires full-scale, time consuming ANN training on each specific structure. Disadvantage of particularly trained ANN algorithm is in its non-transferability to any other object. A new ANN-based AE source location approach is proposed in this paper to overcome such limitation. The method replaces standard arrival time differences at the ANN inputs by so called signal arrival time profiles, independent on material and scale changes. The ANN training can be also performed theoretically on geometrical models and learned ANN is then applied on real structures with different dimensions and materials. Such approach enables considerable extension of ANN application possibilities. The use of new AE source location method is illustrated on experimental data obtained during aircraft structure part testing. AE localization procedures using artificial neural networks (ANN) represent extremely effective alternative to classical triangulation methods. Nevertheless, their application always requires full-scale, time consuming ANN training on each specific structure. Disadvantage of particularly trained ANN algorithm is in its non-transferability to any other object. A new ANN-based AE source location approach is proposed in this paper to overcome such limitation. The method replaces standard arrival time differences at the ANN inputs by so called signal arrival time profiles, independent on material and scale changes. The ANN training can be also performed theoretically on geometrical models and learned ANN is then applied on real structures with different dimensions and materials. Such approach enables considerable extension of ANN application possibilities. The use of new AE source location method is illustrated on experimental data obtained during aircraft structure part testing. (en)
Title	Neural network AE source location apart from structure size and material Neural network AE source location apart from structure size and material (en)
skos:prefLabel	Neural network AE source location apart from structure size and material Neural network AE source location apart from structure size and material (en)
skos:notation	RIV/61388998:_____/10:00349882!RIV11-GA0-61388998
http://linked.open...avai/riv/aktivita	P Z
http://linked.open...avai/riv/aktivity	P(FR-TI1/274), P(GAP104/10/1430), Z(AV0Z20760514)
http://linked.open...vai/riv/dodaniDat	2011
http://linked.open...aciTvurceVysledku	Blaháček, Michal Chlada, Milan Převorovský, Zdeněk
http://linked.open.../riv/druhVysledku	D - Článek ve sborníku
http://linked.open...iv/duvernostUdaju	S - Úplné a pravdivé údaje nepodléhající ochraně podle zvláštních právních předpisů
http://linked.open...titaPredkladatele	Ústav termomechaniky AV ČR, v. v. i.
http://linked.open...dnocenehoVysledku	274501
http://linked.open...ai/riv/idVysledku	RIV/61388998:_____/10:00349882
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	AE source location; artificial neural networks; arrival time profiles (en)
http://linked.open.../riv/klicoveSlovo	artificial neural networks arrival time profiles AE source location
http://linked.open...ontrolniKodProRIV	[2316A8C42ACE]
http://linked.open...v/mistoKonaniAkce	Vídeň
http://linked.open...i/riv/mistoVydani	Vienna
http://linked.open...i/riv/nazevZdroje	29th Europen Conference on Acoustic Emission Testing
http://linked.open...in/vavai/riv/obor	BI
http://linked.open...ichTvurcuVysledku	3 (xsd:int)
http://linked.open...cetTvurcuVysledku	3 (xsd:int)
http://linked.open...vavai/riv/projekt	*Evaluation of SHM methods and its integration into aircraft maintenance system Damage Monitoring of Building Structure Components by Nonlinear Ultrasonic Spectroscopy
http://linked.open...UplatneniVysledku	2010
http://linked.open...iv/tvurceVysledku	Převorovský, Zdeněk Chlada, Milan Blaháček, Michal
http://linked.open...vavai/riv/typAkce	EUR - Evropská
http://linked.open.../riv/zahajeniAkce	2010-09-08 (xsd:date)
http://linked.open...n/vavai/riv/zamer	Complex dynamical systems in thermodynamics, fluid and solid mechanics
number of pages	8 (xsd:int)
http://purl.org/ne...btex#hasPublisher	TÚV Austria
https://schema.org/isbn	978-3-200-01956-0
is http://linked.open...avai/riv/vysledek of	Neural network AE source location apart from structure size and material Neural network AE source location apart from structure size and material Neural network AE source location apart from structure size and material

Faceted Search & Find service v1.16.118 as of Jun 21 2024

Alternative Linked Data Documents: ODE Content Formats:

RDF

ODATA

Microdata

About

OpenLink Virtuoso version 07.20.3240 as of Jun 21 2024, on Linux (x86_64-pc-linux-gnu), Single-Server Edition (126 GB total memory, 35 GB memory in use)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2024 OpenLink Software