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المؤلفAvci O.
المؤلفAbdeljaber O.
المؤلفKiranyaz, Mustafa Serkan
المؤلفInman D.
تاريخ الإتاحة2022-04-26T12:31:21Z
تاريخ النشر2020
اسم المنشورConference Proceedings of the Society for Experimental Mechanics Series
المصدرScopus
المعرّفhttp://dx.doi.org/10.1007/978-3-030-12684-1_24
معرّف المصادر الموحدhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85065980544&doi=10.1007%2f978-3-030-12684-1_24&partnerID=40&md5=246842eac559bcceec6bfdb65fd6a188
معرّف المصادر الموحدhttp://hdl.handle.net/10576/30616
الملخصThe use of self-organizing maps and artificial neural networks for structural health monitoring is presented in this paper. The authors recently developed a nonparametric structural damage detection algorithm for extracting damage indices from the ambient vibration response of a structure. The algorithm is based on self-organizing maps with a multilayer feedforward pattern recognition neural network. After the training of the self-organizing maps, the algorithm was tested analytically under various damage scenarios based on stiffness reduction of beam members and boundary condition changes of a grid structure. The results indicated that proposed algorithm can successfully locate and quantify damage on the structure.
اللغةen
الناشرSpringer New York LLC
الموضوعConformal mapping
Damage detection
Modal analysis
Neural networks
Pattern recognition
Personnel training
Structural analysis
Structural dynamics
Structural health monitoring
Ambient vibrations
Damage localization
Damage scenarios
Grid structures
Multilayer feedforward
Non-parametric
Stiffness reduction
Structural damage detection
Self organizing maps
العنوانStructural health monitoring with self-organizing maps and artificial neural networks
النوعConference Paper
الصفحات237-246
dc.accessType Abstract Only


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