Structural Health Monitoring with Self-Organizing Maps and Artificial Neural Networks
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| Název: | Structural Health Monitoring with Self-Organizing Maps and Artificial Neural Networks |
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| Autoři: | Avci O., Abdeljaber O., Kiranyaz, Mustafa Serkan, Inman D. |
| Zdroj: | Topics in Modal Analysis & Testing, Volume 8 ISBN: 9788743803577 |
| Informace o vydavateli: | River Publishers, 2025. |
| Rok vydání: | 2025 |
| Témata: | Structural damage detection, Structural health monitoring, Ambient vibrations, Damage localization, Multilayer feedforward, Modal analysis, 0211 other engineering and technologies, Structural analysis, 02 engineering and technology, Damage detection, Damage scenarios, Non-parametric, Conformal mapping, 0201 civil engineering, Pattern recognition, Structural dynamics, Stiffness reduction, Neural networks, Grid structures, Personnel training, Self organizing maps |
| Popis: | The 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. |
| Druh dokumentu: | Part of book or chapter of book Other literature type Conference object |
| Jazyk: | English |
| DOI: | 10.1007/978-3-030-12684-1_24 |
| Přístupová URL adresa: | https://link.springer.com/chapter/10.1007%2F978-3-030-12684-1_24 http://www.diva-portal.org/smash/record.jsf?pid=diva2:1362692 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85065980544&doi=10.1007/978-3-030-12684-1_24&partnerID=40&md5=246842eac559bcceec6bfdb65fd6a188 https://hdl.handle.net/10576/30616 |
| Rights: | Springer TDM |
| Přístupové číslo: | edsair.doi.dedup.....6e9419c90990343373d6b8864c5ea0a9 |
| Databáze: | OpenAIRE |
Nájsť tento článok vo Web of Science | Abstrakt: | The 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. |
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| DOI: | 10.1007/978-3-030-12684-1_24 |