Details
| Original language | English |
|---|---|
| Title of host publication | Experimental Vibration Analysis for Civil Engineering Structures |
| Subtitle of host publication | EVACES 2023 - Volume 2 |
| Editors | Maria Pina Limongelli, Pier Francesco Giordano, Carmelo Gentile, Said Quqa, Alfredo Cigada |
| Pages | 401–410 |
| Number of pages | 10 |
| ISBN (electronic) | 978-3-031-39117-0 |
| Publication status | Published - 2023 |
Publication series
| Name | Lecture Notes in Civil Engineering |
|---|---|
| Volume | 433 LNCE |
| ISSN (Print) | 2366-2557 |
| ISSN (electronic) | 2366-2565 |
Abstract
In the context of structural health monitoring (SHM), it is stated that changing environmental conditions (ECs) affect the structure of interest. This fact makes it difficult to distinguish between structural changes caused by damage and those caused by changing ECs. This paper presents a simple physics-informed Gaussian process (GP) to predict the natural frequencies of a lattice tower structure for damage detection. It explores the idea of modelling the effects of different ECs rather than, for example, classifying them. For this purpose, ECs in terms of wind speed, humidity and temperature are used as inputs to a GP to estimate the first two bending modes in the x- and y-directions of the structure. Observed dependencies between inputs and outputs are incorporated by using basis functions to obtain a physically informed GP and hence a grey-box model. To use the estimations and the related confidence intervals as damage-sensitive features, the difference to the measured data is calculated and a threshold for subsequent damage detection is defined. The results are validated using the Leibniz University Test Structure for Monitoring (LUMO), an outdoor lattice tower. It is found that only a small amount of training data is required to achieve acceptable accuracy. Furthermore, it is shown that the presented approach can be used for the detection of artificially induced damage.
Keywords
- Damage detection, Data normalisation, Gaussian process regression, Grey-box modelling
ASJC Scopus subject areas
- Engineering(all)
- Civil and Structural Engineering
Cite this
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Experimental Vibration Analysis for Civil Engineering Structures: EVACES 2023 - Volume 2. ed. / Maria Pina Limongelli; Pier Francesco Giordano; Carmelo Gentile; Said Quqa; Alfredo Cigada. 2023. p. 401–410 (Lecture Notes in Civil Engineering; Vol. 433 LNCE).
Research output: Chapter in book/report/conference proceeding › Contribution to book/anthology › Research › peer review
}
TY - CHAP
T1 - Investigations Towards Physics-Informed Gaussian Process Regression for the Estimation of Modal Parameters of a Lattice Tower Under Environmental Conditions
AU - Möller, Sören
AU - Jonscher, Clemens
AU - Grießmann, Tanja
AU - Rolfes, Raimund
N1 - The authors greatly acknowledge the financial support provided by Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) - CRC 1463, subproject C02.
PY - 2023
Y1 - 2023
N2 - In the context of structural health monitoring (SHM), it is stated that changing environmental conditions (ECs) affect the structure of interest. This fact makes it difficult to distinguish between structural changes caused by damage and those caused by changing ECs. This paper presents a simple physics-informed Gaussian process (GP) to predict the natural frequencies of a lattice tower structure for damage detection. It explores the idea of modelling the effects of different ECs rather than, for example, classifying them. For this purpose, ECs in terms of wind speed, humidity and temperature are used as inputs to a GP to estimate the first two bending modes in the x- and y-directions of the structure. Observed dependencies between inputs and outputs are incorporated by using basis functions to obtain a physically informed GP and hence a grey-box model. To use the estimations and the related confidence intervals as damage-sensitive features, the difference to the measured data is calculated and a threshold for subsequent damage detection is defined. The results are validated using the Leibniz University Test Structure for Monitoring (LUMO), an outdoor lattice tower. It is found that only a small amount of training data is required to achieve acceptable accuracy. Furthermore, it is shown that the presented approach can be used for the detection of artificially induced damage.
AB - In the context of structural health monitoring (SHM), it is stated that changing environmental conditions (ECs) affect the structure of interest. This fact makes it difficult to distinguish between structural changes caused by damage and those caused by changing ECs. This paper presents a simple physics-informed Gaussian process (GP) to predict the natural frequencies of a lattice tower structure for damage detection. It explores the idea of modelling the effects of different ECs rather than, for example, classifying them. For this purpose, ECs in terms of wind speed, humidity and temperature are used as inputs to a GP to estimate the first two bending modes in the x- and y-directions of the structure. Observed dependencies between inputs and outputs are incorporated by using basis functions to obtain a physically informed GP and hence a grey-box model. To use the estimations and the related confidence intervals as damage-sensitive features, the difference to the measured data is calculated and a threshold for subsequent damage detection is defined. The results are validated using the Leibniz University Test Structure for Monitoring (LUMO), an outdoor lattice tower. It is found that only a small amount of training data is required to achieve acceptable accuracy. Furthermore, it is shown that the presented approach can be used for the detection of artificially induced damage.
KW - Damage detection
KW - Data normalisation
KW - Gaussian process regression
KW - Grey-box modelling
UR - http://www.scopus.com/inward/record.url?scp=85174808056&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-39117-0_41
DO - 10.1007/978-3-031-39117-0_41
M3 - Contribution to book/anthology
SN - 978-3-031-39116-3
T3 - Lecture Notes in Civil Engineering
SP - 401
EP - 410
BT - Experimental Vibration Analysis for Civil Engineering Structures
A2 - Limongelli, Maria Pina
A2 - Giordano, Pier Francesco
A2 - Gentile, Carmelo
A2 - Quqa, Said
A2 - Cigada, Alfredo
ER -