Nonparametric structural damage detection algorithm for ambient vibration response: Utilizing artificial neural networks and self-organizing maps
Author | Abdeljaber, Osama |
Author | Avci, Onur |
Available date | 2021-09-01T10:03:28Z |
Publication Date | 2016 |
Publication Name | Journal of Architectural Engineering |
Resource | Scopus |
Abstract | This study presentes a new nonparametric structural damage detection algorithm that integrates self-organizing maps with a pattern-recognition neural network to quantify and locate structural damage. In this algorithm, self-organizing maps are used to extract a number of damage indices from the ambient vibration response of the monitored structure. The presented study is unique because it demonstrates the development of a nonparametric vibration-based damage detection algorithm that utilizes self-organizing maps to extract meaningful damage indices from ambient vibration signals in the time domain. The ability of the algorithm to identify damage was demonstrated analytically using a finite-element model of a hot-rolled steel grid structure. The algorithm successfully located the structural damage under several damage cases, including damage resulting from local stiffness loss in members and damage resulting from changes in boundary conditions. A sensitivity study was also conducted to evaluate the effects of noise on the computed damage indices. The algorithm was proved to be successful even when the signals are noise-contaminated. 2016 American Society of Civil Engineers. |
Language | en |
Publisher | American Society of Civil Engineers (ASCE) |
Subject | Conformal mapping Finite element method Pattern recognition Self organizing maps Signal detection Structural analysis Structural health monitoring Ambient vibrations Artificial neural network algorithm Hot rolled steels Non-parametric Sensitivity studies Structural damage detection Structural damages Vibration-based damage detection Damage detection |
Type | Article |
Issue Number | 2 |
Volume Number | 22 |
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Civil & Architectural Engineering [778 items ]