A New Cloud-Based Software for Automated SHM of Civil Structures

Rune Brincker*, Sandro Amador, Emmanouil Lydakis

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

The principle of the cloud-based Flamenco software is that the operating vibration response data is uploaded by the owner of the structure, then the modal parameters are automatically extracted, and the results are visualized by the owners on a web browser (like Google Chrome, Firefox, etc.). The software consists of a cloud-based web application with front-end and back-end data, meaning that the clients will always have access to its latest version, regardless of the operating system installed on their computers. Since it is essential for the owner of the structure to nondisclose his operational data and the extracted information, only the owner has access to these data. In this chapter, the principles for implementing the OMA extraction features are outlined, and how to check the operating data for sensor errors and how to remove influence from time-varying operating conditions are also explained. The software is illustrated on a simple case, where operating data from a wind-loaded structure is analyzed.
Original languageEnglish
Title of host publicationDynamics of Civil Structures : Volume 2. Proceedings of the 41st IMAC, A Conference and Exposition on Structural Dynamics 2023
EditorsH.Y. Noh, M. Whelan, P.S. Harvey
Volume2
PublisherSpringer
Publication date2023
Pages183-189
ISBN (Print)978-3-031-36662-8
ISBN (Electronic)978-3-031-36663-5
DOIs
Publication statusPublished - 2023
EventSociety for Experimental Mechanics Annual Conference and Exposition - Orlando, United States
Duration: 5 Jun 20238 Jun 2023

Conference

ConferenceSociety for Experimental Mechanics Annual Conference and Exposition
Country/TerritoryUnited States
CityOrlando
Period05/06/202308/06/2023
SeriesConference Proceedings of the Society for Experimental Mechanics Series
Volume2
ISSN2191-5644

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