Please use this identifier to cite or link to this item: http://hdl.handle.net/10261/11610
Share/Export:
logo share SHARE BASE
Visualizar otros formatos: MARC | Dublin Core | RDF | ORE | MODS | METS | DIDL | DATACITE
Title

Sand/Cement ratio evaluation on mortar using neural network and ultrasonic transmission inspection

AuthorsMolero Armenta, Miguel Ángel; Hernández, M. G.; Izquierdo, M. A. G.; Fuente, J. V.; Anaya Velayos, José Javier
Keywordsultrasonic signal processing
material characterization
NDT
neural network application
Issue Date16-Mar-2009
AbstractThe quality and degradation state of building materials can be determined by means of nondestructive testing (NDT). These materials are composed by a cementitious matrix and several aggregates, generally sand and gravel. Sand/cement ratio (s/c) provides the final material quality; however, the sand content can mask the matrix properties in a nondestructive measurement. This work presents an ultrasonic evaluation of the mortar sand content. This evaluation is carried out with several mortar probes which have been varied both, in the quality of the cementitious matrix, and in the s/c ratio. This ratio has been determined by the ultrasonic transmission inspection information with different transducers. Statistical principal component analysis (PCA) in order to reduce the dimension of the captured traces is applied. Feed-forward neural networks have been trained using a reduced PCA and the outputs of the network allow displaying a false color map that shows the mortar probes (s/c) distribution.
Publisher version (URL)http://dx.doi.org/10.3728/ICUltrasonics.2007.Vienna.1532_molero
http://papers.icultrasonics.org/1532_molero.pdf
URIhttp://hdl.handle.net/10261/11610
DOI10.3728/ICUltrasonics.2007.Vienna.1532_molero
Appears in Collections:(IAI) Comunicaciones congresos

Files in This Item:
File Description SizeFormat
1532_molero.pdf263,8 kBAdobe PDFThumbnail
View/Open
Show full item record
Review this work

Page view(s)

423
checked on May 17, 2022

Download(s)

288
checked on May 17, 2022

Google ScholarTM

Check

Altmetric

Dimensions


WARNING: Items in Digital.CSIC are protected by copyright, with all rights reserved, unless otherwise indicated.