CHECKING THE HOMOGENEITY OF CONCRETE USING ARTIFICIAL NEURAL NETWORK

This paper proposes a manner to verify the concrete samples homogeneity using artificial neural networks. This method determines the percentages of different areas of component materials visible at top and bottom of a concrete cylinder having 20 cm diameter and 20 cm height. The materials that have...

Full description

Saved in:
Bibliographic Details
Published inBuletinul Institutului Politehnic din Iași. Secția 6, Construcții, arhitectura Vol. 61; no. 3; p. 83
Main Authors Pandelea, Alexandrina Elena, Budescu, Mihai, Covatariu, Gabriela, Taran, Rares George
Format Journal Article
LanguageEnglish
Published Iasi Gheorghe Asachi Technical Universityi of Jassy 01.05.2015
Subjects
Aggregates
Algorithms
Artificial neural networks
Concretes
Cylinders
Homogeneity
Neural networks
Pixels
Online AccessGet full text

Cover

More Information
Summary:This paper proposes a manner to verify the concrete samples homogeneity using artificial neural networks. This method determines the percentages of different areas of component materials visible at top and bottom of a concrete cylinder having 20 cm diameter and 20 cm height. The materials that have been achieved are rubber grains, aggregates and mineral matrix. The training of the neural network was realise by using backpropagation algorithm and then, in order to separate the regions of interest was used Levenberg - Marquardt algorithm. As a neural network input data were used photos having 258 ×170 pixels resolution achieved both on the both sides of the cylinder.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:1224-3884
2068-4762