Corroboration of NDT and deconvolution neural networks for pedestrian bridge health assessment

This paper describes the specific application of the non-destructive testing methods of visual inspection and ground penetrating radar (GPR) to a pedestrian bridge in Izmir, Turkey. The paper concentrates on the implementation of a deconvolution neural network (DNN) which is a procedure that employs...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:Nondestructive testing and evaluation Ročník 30; číslo 1; s. 89 - 103
Hlavní autoři: Kilic, Gokhan, Unluturk, Mehmet S.
Médium: Journal Article
Jazyk:angličtina
Vydáno: Abingdon Taylor & Francis 02.01.2015
Taylor & Francis Ltd
Témata:
Algorithms
artificial neural network
Assessments
back-propagation learning algorithm
Bridges
Cracks
Decisions
Deconvolution
Ground penetrating radar
health monitoring and assessment
Life expectancy
Moisture
Neural networks
Nondestructive testing
Pedestrian bridges
Pedestrians
Izmir Turkey
ISSN:1058-9759, 1477-2671
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí:This paper describes the specific application of the non-destructive testing methods of visual inspection and ground penetrating radar (GPR) to a pedestrian bridge in Izmir, Turkey. The paper concentrates on the implementation of a deconvolution neural network (DNN) which is a procedure that employs neural network algorithms. By introducing collected GPR data to the DNN, the existence and location of cracks, rebar and moisture ingress on pedestrian pathways can reliably be located, thus providing superior information on which decisions relating to the functionality and life expectancy of a structure can be formulated. This study will be of benefit to engineers in providing a detailed and dependable assessment of the current state of structures such as pedestrian bridges.
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
content type line 23
ISSN:1058-9759
1477-2671
DOI:10.1080/10589759.2014.1002839