OMA of a High-Rise TV Tower Using the Novel Poly-reference Complex Frequency Modal Identification Technique Formulated in Modal Model

Topics in Modal Analysis & Parameter Identification: Conference Proceedings of the Society for Experimental Mechanics Series (SEM 2023). Vol.9 2024
Sandro Amador D.R., Līga Gaile, Emmanouil Lydakis, Rune Brincker

When it comes to multi-dataset Operational Modal Analysis (OMA) of large civil structures, the main goal is to clearly identify the global vibration modes in a very accurate and robust manner. In this chapter, a new frequency domain identification technique is applied to the vibration responses of an outstanding 363-m high television and radio transmission tower, i.e., the Riga TV Tower located at the city of Riga, Latvia. The vibration data was collected during a 3-day testing campaign where a total of 6 datasets were collected at different storeys of the structure by means of two independent measurement systems consisting of two 3D vibration sensors each. The main advantage of the identification technique applied to the tower’s vibration data with regard to the existing approaches is that the former provides clearer stabilization diagrams, facilitating the identification of the physical modes of the tested structures. The application of the novel modal identification technique to tower’s response records led to a clear diagram, from which the most important global vibration modes were easily identified.

Keywords
OMA · Multi-dataset · Modal identification · TV tower · Clear stabilization
DOI
10.1007/978-3-031-34942-3_4
Hyperlink
https://link.springer.com/chapter/10.1007/978-3-031-34942-3_4

Amador D.R., S., Gaile, L., Lydakis, E., Brincker, R. OMA of a High-Rise TV Tower Using the Novel Poly-reference Complex Frequency Modal Identification Technique Formulated in Modal Model. In: Topics in Modal Analysis & Parameter Identification: Conference Proceedings of the Society for Experimental Mechanics Series (SEM 2023). Vol.9, United States of America, Austin, 13-16 February, 2023. Cham: Springer Nature Switzerland AG, 2024, pp.41-48. ISBN 978-3-031-34941-6. e-ISBN 978-3-031-34942-3. ISSN 2191-5652. e-ISSN 2191-5644. Available from: doi:10.1007/978-3-031-34942-3_4

Publication language
English (en)