Details
| Original language | English |
|---|---|
| Title of host publication | 9th IOMAC International Operational Modal Analysis Conference, Proceedings |
| Editors | Carlos E. Ventura, Mehrtash Motamedi, Alexander Mendler, Manuel Aenlle-Lopez |
| Pages | 77-90 |
| Number of pages | 14 |
| ISBN (electronic) | 9788409443369 |
| Publication status | Published - 2022 |
| Event | 9th International Operational Modal Analysis Conference, IOMAC 2022 - Vancouver, Canada Duration: 3 Jul 2022 → 6 Jul 2022 |
Publication series
| Name | 9th IOMAC International Operational Modal Analysis Conference, Proceedings |
|---|
Abstract
Identifying the modal properties of mechanical engineering systems while these are under operating conditions is still associated with major challenges, especially when said operation is induced by rotation of components. In this case, ambient vibration excitation, which is typically assumed for the application of output only techniques, is superposed by a deterministic periodic excitation component. This paper studies different techniques to perform an operational modal analysis in this particular situation. The methods are applied to an axial compressor test rig at the Institute of Turbomachinery and Fluid-Dynamics. Among them, three approaches, the Hilbert-Huang transform, the Bayesian OMA, and the stochastic subspace identification, are investigated. For the stochastic subspace identification, two different pole picking techniques to automatize the selection of stable poles from the stability diagram are studied. Furthermore, various approaches to deal with the harmonic excitation, which can lead to falsely identified modal parameters in the analysis process, are presented and applied to the data sets. Measurements at different rotational speeds of the rotor were collected and are used for the analysis. The results are summarized and the relative strengths and weaknesses of the different methods are discussed. The results obtained in this study are a first step towards a digital model to monitor the vibration behavior of rotating machinery using OMA techniques.
Keywords
- axial compressor, harmonic detection, Hilbert-Huang transform, pole picking, stochastic subspace identification
ASJC Scopus subject areas
- Engineering(all)
- Mechanical Engineering
- Engineering(all)
- Mechanics of Materials
- Engineering(all)
- Building and Construction
- Physics and Astronomy(all)
- Instrumentation
Cite this
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9th IOMAC International Operational Modal Analysis Conference, Proceedings. ed. / Carlos E. Ventura; Mehrtash Motamedi; Alexander Mendler; Manuel Aenlle-Lopez. 2022. p. 77-90 (9th IOMAC International Operational Modal Analysis Conference, Proceedings).
Research output: Chapter in book/report/conference proceeding › Conference contribution › Research › peer review
}
TY - GEN
T1 - comparison of different oma techniques and their application to an axial compressor test rig
AU - Amer, Mona
AU - Wallaschek, Joerg
AU - Seume, Joerg R.
AU - Ventura, Carlos E.
PY - 2022
Y1 - 2022
N2 - Identifying the modal properties of mechanical engineering systems while these are under operating conditions is still associated with major challenges, especially when said operation is induced by rotation of components. In this case, ambient vibration excitation, which is typically assumed for the application of output only techniques, is superposed by a deterministic periodic excitation component. This paper studies different techniques to perform an operational modal analysis in this particular situation. The methods are applied to an axial compressor test rig at the Institute of Turbomachinery and Fluid-Dynamics. Among them, three approaches, the Hilbert-Huang transform, the Bayesian OMA, and the stochastic subspace identification, are investigated. For the stochastic subspace identification, two different pole picking techniques to automatize the selection of stable poles from the stability diagram are studied. Furthermore, various approaches to deal with the harmonic excitation, which can lead to falsely identified modal parameters in the analysis process, are presented and applied to the data sets. Measurements at different rotational speeds of the rotor were collected and are used for the analysis. The results are summarized and the relative strengths and weaknesses of the different methods are discussed. The results obtained in this study are a first step towards a digital model to monitor the vibration behavior of rotating machinery using OMA techniques.
AB - Identifying the modal properties of mechanical engineering systems while these are under operating conditions is still associated with major challenges, especially when said operation is induced by rotation of components. In this case, ambient vibration excitation, which is typically assumed for the application of output only techniques, is superposed by a deterministic periodic excitation component. This paper studies different techniques to perform an operational modal analysis in this particular situation. The methods are applied to an axial compressor test rig at the Institute of Turbomachinery and Fluid-Dynamics. Among them, three approaches, the Hilbert-Huang transform, the Bayesian OMA, and the stochastic subspace identification, are investigated. For the stochastic subspace identification, two different pole picking techniques to automatize the selection of stable poles from the stability diagram are studied. Furthermore, various approaches to deal with the harmonic excitation, which can lead to falsely identified modal parameters in the analysis process, are presented and applied to the data sets. Measurements at different rotational speeds of the rotor were collected and are used for the analysis. The results are summarized and the relative strengths and weaknesses of the different methods are discussed. The results obtained in this study are a first step towards a digital model to monitor the vibration behavior of rotating machinery using OMA techniques.
KW - axial compressor
KW - harmonic detection
KW - Hilbert-Huang transform
KW - pole picking
KW - stochastic subspace identification
UR - http://www.scopus.com/inward/record.url?scp=85147843712&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85147843712
T3 - 9th IOMAC International Operational Modal Analysis Conference, Proceedings
SP - 77
EP - 90
BT - 9th IOMAC International Operational Modal Analysis Conference, Proceedings
A2 - Ventura, Carlos E.
A2 - Motamedi, Mehrtash
A2 - Mendler, Alexander
A2 - Aenlle-Lopez, Manuel
T2 - 9th International Operational Modal Analysis Conference, IOMAC 2022
Y2 - 3 July 2022 through 6 July 2022
ER -