Title:
Neural networks in the NDT identification of the strength of concrete
Author(s):
K. Schabowicz
Publication:
KILW
Volume:
51
Issue:
3
Appears on pages(s):
371-382
Keywords:
non destructive testing, strength
DOI:
Date:
7/1/2005
Abstract:
This paper presents an application of artificial neural networks to concrete compression strength identification based on parameters determined by nondestructive methods. Three ordinary concretes and three high-performance concretes with a compression strength of 24-105 MPa were investigated. The parameters determined by nondestructive methods, i.e. the ultrasonic method, sclerometric methods and the pull-out method, and the age and bulk density of the concretes were used. A neural network with the Levenberg-Marquardt algorithm was chosen from several networks and successfully applied. The paper presents a methodology for the neural identification of the compression strength of concrete and some results of the investigation.