Quantification Of Structural Damage With Self-Organizing Maps
Keywords
Damage detection; Damage identification; Modal testing; Self organizing maps; Structural health monitoring
Abstract
One of the main tasks in structural health monitoring process is to create reliable algorithms that are capable of translating the measured response into meaningful information reflecting the actual condition of the monitored structure. The authors have recently introduced a novel unsupervised vibration-based damage detection algorithm that utilizes selforganizing maps to quantify structural damage and assess the overall condition of structures. Previously, this algorithm had been tested using the experimental data of Phase II Experimental Benchmark Problem of Structural Health Monitoring, introduced by the IASC (International Association for Structural Control) and ASCE (American Society of Civil Engineers). In this paper, the ability of this algorithm to quantify structural damage is tested analytically using an experimentally validated finite element model of a laboratory structure constructed at Qatar University.
Publication Date
1-1-2016
Publication Title
Conference Proceedings of the Society for Experimental Mechanics Series
Volume
7
Number of Pages
47-57
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
DOI Link
https://doi.org/10.1007/978-3-319-29956-3_5
Copyright Status
Unknown
Socpus ID
84978674876 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/84978674876
STARS Citation
Abdeljaber, Osama; Avci, Onur; Do, Ngoan Tien; Gul, Mustafa; and Celik, Ozan, "Quantification Of Structural Damage With Self-Organizing Maps" (2016). Scopus Export 2015-2019. 4461.
https://stars.library.ucf.edu/scopus2015/4461