TY  - THES
A1  - Alkam, Feras
T1  - Vibration-based Monitoring of Concrete Catenary Poles using Bayesian Inference
N2  - This work presents a robust status monitoring approach for detecting damage in cantilever structures based on logistic functions. Also, a stochastic damage identification approach based on changes of eigenfrequencies is proposed. The proposed algorithms are verified using catenary poles of electrified railways track. The proposed damage features overcome the limitation of frequency-based damage identification methods available in the literature, which are valid to detect damage in structures to Level 1 only. Changes in eigenfrequencies of cantilever structures are enough to identify possible local damage at Level 3, i.e., to cover damage detection, localization, and quantification. The proposed algorithms identified the damage with relatively small errors, even at a high noise level.
KW  - Parameteridentifikation
KW  - Bayesian Inference, Uncertainty Quantification
KW  - Inverse Problems
KW  - Damage Identification
KW  - Concrete catenary pole
KW  - SHM
KW  - Inverse Probleme
KW  - Bayes’schen Inferenz
KW  - Unschärfequantifizierung
KW  - Schadenerkennung
KW  - Oberleitungsmasten
Y1  - 2021
UR  - https://e-pub.uni-weimar.de/opus4/frontdoor/index/index/docId/4433
UR  - https://nbn-resolving.org/urn:nbn:de:gbv:wim2-20210526-44338
UR  - https://asw-verlage.de/katalog/vibration_based_monitoring_of_co-2363.html
VL  - 2021
PB  - Bauhaus-Universitätsverlag
CY  - Weimar
ER  -