Details
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 10th International Operational Modal Analysis Conference (IOMAC 2024) |
| Editors | Carlo Rainieri, Carmelo Gentile, Manuel Aenlle López |
| Pages | 87-94 |
| Number of pages | 8 |
| ISBN (electronic) | 978-3-031-61425-5 |
| Publication status | Published - 22 Jun 2024 |
Publication series
| Name | Lecture Notes in Civil Engineering |
|---|---|
| Volume | 515 LNCE |
| ISSN (Print) | 2366-2557 |
| ISSN (electronic) | 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.
Keywords
- Autocovariance function, Closely spaced modes, Damage detection, Environmental or operational variability, Spatiotemporal correlation, Structural health monitoring
ASJC Scopus subject areas
- Engineering(all)
- Civil and Structural Engineering
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Proceedings of the 10th International Operational Modal Analysis Conference (IOMAC 2024). ed. / Carlo Rainieri; Carmelo Gentile; Manuel Aenlle López. 2024. p. 87-94 Chapter 9 (Lecture Notes in Civil Engineering; Vol. 515 LNCE).
Research output: Chapter in book/report/conference proceeding › Contribution to book/anthology › Research › peer review
}
TY - CHAP
T1 - Damage Detection with Closely Spaced Modes Using Autocovariance Functions
AU - Kullaa, Jyrki
AU - Jonscher, Clemens
AU - Liesecke, Leon
AU - Rolfes, Raimund
N1 - Publisher Copyright: © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
PY - 2024/6/22
Y1 - 2024/6/22
N2 - 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.
AB - 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.
KW - Autocovariance function
KW - Closely spaced modes
KW - Damage detection
KW - Environmental or operational variability
KW - Spatiotemporal correlation
KW - Structural health monitoring
UR - http://www.scopus.com/inward/record.url?scp=85200516390&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-61425-5_9
DO - 10.1007/978-3-031-61425-5_9
M3 - Contribution to book/anthology
SN - 978-3-031-61424-8
T3 - Lecture Notes in Civil Engineering
SP - 87
EP - 94
BT - Proceedings of the 10th International Operational Modal Analysis Conference (IOMAC 2024)
A2 - Rainieri, Carlo
A2 - Gentile, Carmelo
A2 - Aenlle López, Manuel
ER -