Damage Detection with Closely Spaced Modes Using Autocovariance Functions

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OriginalspracheEnglisch
Titel des SammelwerksProceedings of the 10th International Operational Modal Analysis Conference (IOMAC 2024)
Herausgeber/-innenCarlo Rainieri, Carmelo Gentile, Manuel Aenlle López
Seiten87-94
Seitenumfang8
ISBN (elektronisch)978-3-031-61425-5
PublikationsstatusVeröffentlicht - 22 Juni 2024

Publikationsreihe

NameLecture Notes in Civil Engineering
Band515 LNCE
ISSN (Print)2366-2557
ISSN (elektronisch)2366-2565

Abstract

Monitoring of structures having closely spaced modes is challenging due to issues in system identification and mode tracking. However, these issues are not present if damage detection is performed in the time domain using e.g. raw sensor data or covariance functions. Replacing raw vibration measurement data with autocovariance functions (ACFs) offers many advantages in damage detection. For stationary random excitation, ACFs have the same form as a free decay of the system. Consequently, ACFs of different sensors are spatiotemporally correlated, which can be utilized in damage detection. In case of closely spaced modes, correlation between modal responses is non-negligible, which can make damage detection more difficult. Damage detection with closely spaced modes was explored numerically using a finite element model of a frame structure subject to random excitation and variable environmental conditions. Acceleration measurements were simulated at three positions. Damage was a local stiffness degradation. Also, experimental data of a lattice tower under wind excitation were analyzed. Damage was a stiffness and mass decrease due to removal of bracings. It was found that closely spaced modes or mode crossings did not require any special treatment if damage detection was performed in the time domain.

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Damage Detection with Closely Spaced Modes Using Autocovariance Functions. / Kullaa, Jyrki; Jonscher, Clemens; Liesecke, Leon et al.
Proceedings of the 10th International Operational Modal Analysis Conference (IOMAC 2024). Hrsg. / Carlo Rainieri; Carmelo Gentile; Manuel Aenlle López. 2024. S. 87-94 Chapter 9 (Lecture Notes in Civil Engineering; Band 515 LNCE).

Publikation: Beitrag in Buch/Bericht/Sammelwerk/KonferenzbandBeitrag in Buch/SammelwerkForschungPeer-Review

Kullaa, J, Jonscher, C, Liesecke, L & Rolfes, R 2024, Damage Detection with Closely Spaced Modes Using Autocovariance Functions. in C Rainieri, C Gentile & M Aenlle López (Hrsg.), Proceedings of the 10th International Operational Modal Analysis Conference (IOMAC 2024)., Chapter 9, Lecture Notes in Civil Engineering, Bd. 515 LNCE, S. 87-94. https://doi.org/10.1007/978-3-031-61425-5_9
Kullaa, J., Jonscher, C., Liesecke, L., & Rolfes, R. (2024). Damage Detection with Closely Spaced Modes Using Autocovariance Functions. In C. Rainieri, C. Gentile, & M. Aenlle López (Hrsg.), Proceedings of the 10th International Operational Modal Analysis Conference (IOMAC 2024) (S. 87-94). Artikel Chapter 9 (Lecture Notes in Civil Engineering; Band 515 LNCE). https://doi.org/10.1007/978-3-031-61425-5_9
Kullaa J, Jonscher C, Liesecke L, Rolfes R. Damage Detection with Closely Spaced Modes Using Autocovariance Functions. in Rainieri C, Gentile C, Aenlle López M, Hrsg., Proceedings of the 10th International Operational Modal Analysis Conference (IOMAC 2024). 2024. S. 87-94. Chapter 9. (Lecture Notes in Civil Engineering). doi: 10.1007/978-3-031-61425-5_9
Kullaa, Jyrki ; Jonscher, Clemens ; Liesecke, Leon et al. / Damage Detection with Closely Spaced Modes Using Autocovariance Functions. Proceedings of the 10th International Operational Modal Analysis Conference (IOMAC 2024). Hrsg. / Carlo Rainieri ; Carmelo Gentile ; Manuel Aenlle López. 2024. S. 87-94 (Lecture Notes in Civil Engineering).
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