Quantification of Structural Damage with Self-Organizing Maps

被引:11
作者
Abdeljaber, Osama [1 ]
Avci, Onur [1 ]
Do, Ngoan Tien [2 ]
Gul, Mustafa [2 ]
Celik, Ozan [3 ]
Catbas, F. Necati [3 ]
机构
[1] Qatar Univ, Dept Civil & Architectural Engn, Coll Engn, POB 2713, Doha, Qatar
[2] Univ Alberta, Dept Civil & Environm Engn, Donadeo Innovat Ctr Engn, 9211-116 St NW, Edmonton, AB T6G 2R3, Canada
[3] Univ Cent Florida, Dept Civil Environm & Construct Engn, Cent Florida Blvd, Orlando, FL 32816 USA
来源
STRUCTURAL HEALTH MONITORING, DAMAGE DETECTION & MECHATRONICS, VOL 7 | 2016年
关键词
Self organizing maps; Damage detection; Damage identification; Structural health monitoring; Modal testing; NEURAL-NETWORK APPROACH;
D O I
10.1007/978-3-319-29956-3_5
中图分类号
TH [机械、仪表工业];
学科分类号
120111 [工业工程];
摘要
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 self-organizing 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.
引用
收藏
页码:47 / 57
页数:11
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