Details
| Original language | English |
|---|---|
| Journal | e-Journal of Nondestructive Testing |
| Volume | 29 |
| Issue number | 7 |
| Publication status | Published - 1 Jul 2024 |
Abstract
This study presents a multi-objective model updating technique and its application to a tower structure featuring closely spaced bending modes with the aim of localising structural damage. In structural health monitoring, modal characteristics, such as eigenfrequencies and mode shapes, serve as indicators for damage detection and localisation. Specifically, model updating strategies adjust the local structural stiffness in a finite element model to reduce the difference between these identified modal quantities and the corresponding modal properties of the model. Consequently, the best-fitting structural stiffness properties, which represent the damaged state of the structure, can provide valuable information about the damage that has occurred. Symmetrical tower structures can pose a challenge to model updating approaches as they typically possess closely spaced modes which are difficult to identify due to spatial orientation and alignment uncertainties. Consequently, the direct comparison between the mode shapes of the structure and the model yields poor results, regardless of apparent similarities in the dominant mode shapes. In order to overcome this problem, we adapt the concept of the subspace of order 2 modal assurance criterion (S2MAC), i.e., finding the best representation of a vector in a subspace spanned by two bending modes. By adapting this concept, this study solves mode shape alignment problems between real structures and models, thus allowing a comparison of the actual dominant mode shapes. The method is validated using an experimental 9 m tall lattice tower with reversible damage characteristics. Ambient vibrations of the structure are continuously recorded using acceleration sensors placed at different height levels. Mode shapes and eigenfrequencies, identified using the BAYOMA method, are employed for multi-objective model updating, resulting in multiple Pareto-optimal solutions. The damage localisation is applied to datasets recorded over a time span of several months featuring three different damage positions. The results obtained prove the necessity of a multi-objective approach and the consideration of mode orientation for the application example used.
Keywords
- closely spaced modes, damage localisation, environmental variation, model updating, multi-objective optimisation
ASJC Scopus subject areas
- Health Professions(all)
- Health Information Management
- Computer Science(all)
- Computer Science Applications
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In: e-Journal of Nondestructive Testing, Vol. 29, No. 7, 01.07.2024.
Research output: Contribution to journal › Article › Research
}
TY - JOUR
T1 - Multi-Objective Model Updating of Tower Structures Featuring Closely Spaced Modes
AU - Ragnitz, Jasper
AU - Hofmeister, Benedikt
AU - Jonscher, Clemens
AU - Hübler, Clemens
AU - Rolfes, Raimund
N1 - Publisher Copyright: © 2024 11th European Workshop on Structural Health Monitoring, EWSHM 2024. All rights reserved.
PY - 2024/7/1
Y1 - 2024/7/1
N2 - This study presents a multi-objective model updating technique and its application to a tower structure featuring closely spaced bending modes with the aim of localising structural damage. In structural health monitoring, modal characteristics, such as eigenfrequencies and mode shapes, serve as indicators for damage detection and localisation. Specifically, model updating strategies adjust the local structural stiffness in a finite element model to reduce the difference between these identified modal quantities and the corresponding modal properties of the model. Consequently, the best-fitting structural stiffness properties, which represent the damaged state of the structure, can provide valuable information about the damage that has occurred. Symmetrical tower structures can pose a challenge to model updating approaches as they typically possess closely spaced modes which are difficult to identify due to spatial orientation and alignment uncertainties. Consequently, the direct comparison between the mode shapes of the structure and the model yields poor results, regardless of apparent similarities in the dominant mode shapes. In order to overcome this problem, we adapt the concept of the subspace of order 2 modal assurance criterion (S2MAC), i.e., finding the best representation of a vector in a subspace spanned by two bending modes. By adapting this concept, this study solves mode shape alignment problems between real structures and models, thus allowing a comparison of the actual dominant mode shapes. The method is validated using an experimental 9 m tall lattice tower with reversible damage characteristics. Ambient vibrations of the structure are continuously recorded using acceleration sensors placed at different height levels. Mode shapes and eigenfrequencies, identified using the BAYOMA method, are employed for multi-objective model updating, resulting in multiple Pareto-optimal solutions. The damage localisation is applied to datasets recorded over a time span of several months featuring three different damage positions. The results obtained prove the necessity of a multi-objective approach and the consideration of mode orientation for the application example used.
AB - This study presents a multi-objective model updating technique and its application to a tower structure featuring closely spaced bending modes with the aim of localising structural damage. In structural health monitoring, modal characteristics, such as eigenfrequencies and mode shapes, serve as indicators for damage detection and localisation. Specifically, model updating strategies adjust the local structural stiffness in a finite element model to reduce the difference between these identified modal quantities and the corresponding modal properties of the model. Consequently, the best-fitting structural stiffness properties, which represent the damaged state of the structure, can provide valuable information about the damage that has occurred. Symmetrical tower structures can pose a challenge to model updating approaches as they typically possess closely spaced modes which are difficult to identify due to spatial orientation and alignment uncertainties. Consequently, the direct comparison between the mode shapes of the structure and the model yields poor results, regardless of apparent similarities in the dominant mode shapes. In order to overcome this problem, we adapt the concept of the subspace of order 2 modal assurance criterion (S2MAC), i.e., finding the best representation of a vector in a subspace spanned by two bending modes. By adapting this concept, this study solves mode shape alignment problems between real structures and models, thus allowing a comparison of the actual dominant mode shapes. The method is validated using an experimental 9 m tall lattice tower with reversible damage characteristics. Ambient vibrations of the structure are continuously recorded using acceleration sensors placed at different height levels. Mode shapes and eigenfrequencies, identified using the BAYOMA method, are employed for multi-objective model updating, resulting in multiple Pareto-optimal solutions. The damage localisation is applied to datasets recorded over a time span of several months featuring three different damage positions. The results obtained prove the necessity of a multi-objective approach and the consideration of mode orientation for the application example used.
KW - closely spaced modes
KW - damage localisation
KW - environmental variation
KW - model updating
KW - multi-objective optimisation
UR - http://www.scopus.com/inward/record.url?scp=85202544274&partnerID=8YFLogxK
U2 - 10.58286/29663
DO - 10.58286/29663
M3 - Article
VL - 29
JO - e-Journal of Nondestructive Testing
JF - e-Journal of Nondestructive Testing
SN - 1435-4934
IS - 7
ER -