contributor author | Jun Zhao | |
contributor author | John N. Ivan | |
contributor author | John T. DeWolf | |
date accessioned | 2017-05-08T21:21:07Z | |
date available | 2017-05-08T21:21:07Z | |
date copyright | September 1998 | |
date issued | 1998 | |
identifier other | %28asce%291076-0342%281998%294%3A3%2893%29.pdf | |
identifier uri | http://yetl.yabesh.ir/yetl/handle/yetl/48074 | |
description abstract | Artificial neural networks are efficient computing techniques that are widely used to solve complex problems in many fields. In this study, a counterpropagation neural network is used to locate structural damage for a beam, a frame, and support movements of a beam in its axial direction. The investigation considers a variety of diagnostic parameters, including static displacements, natural frequencies, mode shapes, and other parameters based on mode shapes. The method is first demonstrated on a plane frame, based on static displacements. It is then applied to continuous beams using dynamic properties of structures. The required data are obtained through computer simulation by finite-element analysis. The results demonstrate that these parameters can be used as diagnostic parameters for artificial neural networks in structural engineering. An anticipated application to bridge monitoring is discussed. | |
publisher | American Society of Civil Engineers | |
title | Structural Damage Detection Using Artificial Neural Networks | |
type | Journal Paper | |
journal volume | 4 | |
journal issue | 3 | |
journal title | Journal of Infrastructure Systems | |
identifier doi | 10.1061/(ASCE)1076-0342(1998)4:3(93) | |
tree | Journal of Infrastructure Systems:;1998:;Volume ( 004 ):;issue: 003 | |
contenttype | Fulltext | |