A Non-Destructive Testing Based on Electromagnetic Measurements and Neural Networks for the Inspection of Concrete Structures


Autoria(s): Al Cantara Jr, Naasson P. de; Costa, Danilo C.; Guedes, Diego S.; Sartori, Ricardo; Bastos, Paulo S. S.; Esa, R; Wu, YW
Contribuinte(s)

Universidade Estadual Paulista (UNESP)

Data(s)

20/05/2014

20/05/2014

01/01/2011

Resumo

This paper presents a new non-destructive testing (NDT) for reinforced concrete structures, in order to identify the components of their reinforcement. A time varying electromagnetic field is generated close to the structure by electromagnetic devices specially designed for this purpose. The presence of ferromagnetic materials (the steel bars of the reinforcement) immersed in the concrete disturbs the magnetic field at the surface of the structure. These field alterations are detected by sensors coils placed on the concrete surface. Variations in position and cross section (the size) of steel bars immersed in concrete originate slightly different values for the induced voltages at the coils.. The values for the induced voltages were obtained in laboratory tests, and multi-layer perceptron artificial neural networks with Levemberg-Marquardt training algorithm were used to identify the location and size of the bar. Preliminary results can be considered very good.

Formato

597-602

Identificador

http://dx.doi.org/10.4028/www.scientific.net/AMR.301-303.597

Advanced Measurement and Test, Pts 1-3. Stafa-zurich: Trans Tech Publications Ltd, v. 301-303, p. 597-602, 2011.

1022-6680

http://hdl.handle.net/11449/40120

10.4028/www.scientific.net/AMR.301-303.597

WOS:000307023300107

Idioma(s)

eng

Publicador

Trans Tech Publications Ltd

Relação

Advanced Measurement and Test, Pts 1-3

Direitos

closedAccess

Palavras-Chave #Non-Destructive Testing #Eddy Current Testing #Concrete Structures #Concrete Re nforcement #Artificial Neural Networks
Tipo

info:eu-repo/semantics/conferencePaper