Virtual measurements for exterior vibro-acoustic problems using experimental modal models
Virtual measurements for exterior vibro-acoustic problems using experimental modal models
This paper presents a virtual sensor scheme for vibroacoustic radiation applications based on experimental modal state-space models and sparse measurements. A Kalman filter is used for the estimation combining data from the acoustical and the structural domain together with the numerical modal process model. It is proposed to use Gramians, as an energy-related measure of a system’s observability which enables assessing the observability of the coupled vibroacoustic system in the modal state-space domain and the physical state domain counterpart. This Gramian-based observability metric reveals modes or states of high observability, which ensure good estimation results in the subsequent estimation. The proposed method is validated using an industrial test setup for which, due to its high complexity, modelling with first-principle techniques is not feasible. The estimation results demonstrate improved performance compared to a pure forward use of the identified model, indicating the effectiveness of the virtual sensor approach. Additionally, the newly proposed Gramian-based observability criterion outperforms state-of-the-art metrics for sensor placement in terms of estimation accuracy for particular states of interest, as demonstrated in a sensor placement task. Overall, this paper provides a promising approach for virtual sensing for vibroacoustic applications, enabling accurate and efficient system monitoring and control.
0905 Civil Engineering, 0913 Mechanical Engineering, 0915 Interdisciplinary Engineering, 4006 Communications engineering, 4017 Mechanical engineering, ALGORITHMS, Acoustics, CONTROLLABILITY, Engineering, Engineering, Mechanical, Experimental state-space model, IDENTIFICATION, Kalman filter, OPTIMAL SENSOR, Observability Gramian, Science & Technology, State-estimation, Technology, Vibroacoustics, Virtual sensing
Staiger, Julian
48a3548b-9f05-46f1-a7fc-4b4461121aab
van Ophem, Sjoerd
bb3fb37e-577b-4152-86bc-2248943f882d
Troge, Jan
175f8098-17d3-45b4-923e-fc0b1c4562b2
Naets, Frank
4a1e9ad4-af14-43f2-997a-42f016463358
12 January 2024
Staiger, Julian
48a3548b-9f05-46f1-a7fc-4b4461121aab
van Ophem, Sjoerd
bb3fb37e-577b-4152-86bc-2248943f882d
Troge, Jan
175f8098-17d3-45b4-923e-fc0b1c4562b2
Naets, Frank
4a1e9ad4-af14-43f2-997a-42f016463358
Staiger, Julian, van Ophem, Sjoerd, Troge, Jan and Naets, Frank
(2024)
Virtual measurements for exterior vibro-acoustic problems using experimental modal models.
Mechanical Systems and Signal Processing, 209, [111110].
(doi:10.1016/j.ymssp.2024.111110).
Abstract
This paper presents a virtual sensor scheme for vibroacoustic radiation applications based on experimental modal state-space models and sparse measurements. A Kalman filter is used for the estimation combining data from the acoustical and the structural domain together with the numerical modal process model. It is proposed to use Gramians, as an energy-related measure of a system’s observability which enables assessing the observability of the coupled vibroacoustic system in the modal state-space domain and the physical state domain counterpart. This Gramian-based observability metric reveals modes or states of high observability, which ensure good estimation results in the subsequent estimation. The proposed method is validated using an industrial test setup for which, due to its high complexity, modelling with first-principle techniques is not feasible. The estimation results demonstrate improved performance compared to a pure forward use of the identified model, indicating the effectiveness of the virtual sensor approach. Additionally, the newly proposed Gramian-based observability criterion outperforms state-of-the-art metrics for sensor placement in terms of estimation accuracy for particular states of interest, as demonstrated in a sensor placement task. Overall, this paper provides a promising approach for virtual sensing for vibroacoustic applications, enabling accurate and efficient system monitoring and control.
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More information
Accepted/In Press date: 3 January 2024
e-pub ahead of print date: 12 January 2024
Published date: 12 January 2024
Keywords:
0905 Civil Engineering, 0913 Mechanical Engineering, 0915 Interdisciplinary Engineering, 4006 Communications engineering, 4017 Mechanical engineering, ALGORITHMS, Acoustics, CONTROLLABILITY, Engineering, Engineering, Mechanical, Experimental state-space model, IDENTIFICATION, Kalman filter, OPTIMAL SENSOR, Observability Gramian, Science & Technology, State-estimation, Technology, Vibroacoustics, Virtual sensing
Identifiers
Local EPrints ID: 495140
URI: http://eprints.soton.ac.uk/id/eprint/495140
ISSN: 1096-1216
PURE UUID: b0f3d408-49d2-4663-994a-e4f8766b7d87
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Date deposited: 30 Oct 2024 17:46
Last modified: 31 Oct 2024 03:15
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Author:
Julian Staiger
Author:
Sjoerd van Ophem
Author:
Jan Troge
Author:
Frank Naets
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