dc.contributor.author | Fernández-Navamuel, Ana | |
dc.contributor.author | Zamora-Sánchez, Diego | |
dc.contributor.author | Varona-Poncela, Tomás | |
dc.contributor.author | Jiménez-Fernández, Carlos | |
dc.contributor.author | Díez-Hernández, Jesús | |
dc.contributor.author | García-Sánchez, David | |
dc.contributor.author | Pardo, David | |
dc.date.accessioned | 2021-04-09T13:42:14Z | |
dc.date.available | 2021-04-09T13:42:14Z | |
dc.date.issued | 2021-01-11 | |
dc.identifier.citation | Fernández-Navamuel, Ana, Diego Zamora-Sánchez, Tomás Varona-Poncela, Carlos Jiménez-Fernández, Jesús Díez-Hernández, David García-Sánchez, and David Pardo. “Vibration-Based SHM Strategy for a Real Time Alert System with Damage Location and Quantification.” European Workshop on Structural Health Monitoring (2021): 245–255. doi:10.1007/978-3-030-64594-6_25. | en |
dc.identifier.isbn | 978-303064593-9 | en |
dc.identifier.issn | 2366-2557 | en |
dc.identifier.uri | http://hdl.handle.net/11556/1104 | |
dc.description.abstract | We present a simple and fully automatable vibration-based Structural Health Monitoring (SHM) alert system. The proposed method consists in applying an Automated Frequency Domain Decomposition (AFDD) algorithm to obtain the eigenfrequencies and mode shapes in real time from acceleration measurements, allowing to provide a diagnosis based on a Support Vector Machine algorithm trained with a database of the modal properties in undamaged and damaged scenarios accounting for temperature variability. The result is an alert system for controlling the correct performance of the structure in real time with a simple but efficient approach. Once the alert is triggered, the undamaged mode shapes (which could be previously stored in a database of modal parameters classified by temperature) and the current (damaged) mode shapes, can provide guidance for further application of Finite Element Model Updating (FEMU) techniques. The method is trained and validated with simulations from a FE model that is calibrated employing a genetic algorithm with real data from a short-term vibration measurement campaign on a truss railway bridge in Alicante (Spain). | en |
dc.description.sponsorship | This project has received funding from the European Union’s Horizon 2020 research and innovation program under the grant agreement No 769373 (FORESEE project). This paper reflects only the author’s views. The European Commission and INEA are not responsible for any use that may be made of the information contained therein. | en |
dc.language.iso | eng | en |
dc.publisher | Springer, Cham | en |
dc.title | Vibration-Based SHM Strategy for a Real Time Alert System with Damage Location and Quantification | en |
dc.type | conferenceObject | en |
dc.identifier.doi | 10.1007/978-3-030-64594-6_25 | en |
dc.relation.projectID | info:eu-repo/grantAgreement/EC/H2020/769373/EU/Future proofing strategies FOr RESilient transport networks against Extreme Events/FORESEE | en |
dc.rights.accessRights | embargoedAccess | en |
dc.subject.keywords | Structural health monitoring | en |
dc.subject.keywords | Structural dynamics | en |
dc.subject.keywords | Bridge maintenance | en |
dc.subject.keywords | Machine learning | en |
dc.identifier.essn | 2366-2565 | en |
dc.journal.title | Lecture Notes in Civil Engineering | en |
dc.page.final | 255 | en |
dc.page.initial | 245 | en |
dc.volume.number | 127 | en |
dc.conference.title | EWSHM 2020: European Workshop on Structural Health Monitoring | en |