Noise-robust modal parameter identification and damage assessment for aero-structures

Date published

2024-12-16

Free to read from

2025-03-12

Supervisor/s

Journal Title

Journal ISSN

Volume Title

Publisher

Emerald

Department

Type

Article

ISSN

1748-8842

Format

Citation

Dessena G, Civera M, Pontillo A, et al., (2024) Noise-robust modal parameter identification and damage assessment for aero-structures. Aircraft Engineering and Aerospace Technology, Volume 96, Issue 11, December 2024, pp. 27-36

Abstract

Purpose Ground vibration testing is critical for aircraft design and certification. Fast relaxed vector fitting (FRVF) and Loewner framework (LF), recently extended to modal parameter extraction in mechanical systems to address the computational challenges of time and frequency domain techniques, are applied for damage detection on aeronautically relevant structures.

Design/methodology/approach FRVF and LF are applied to numerical datasets to assess noise robustness and performance for damage detection. Computational efficiency is also evaluated. In addition, they are applied to a novel damage detection benchmark of a high aspect ratio wing, comparing their performance with the state-of-the-art method N4SID.

Findings FRVF and LF detect structural changes effectively; LF exhibits better noise robustness, while FRVF is more computationally efficient.

Practical implications LF is recommended for noisy measurements.

Originality/value To the best of the authors’ knowledge, this is the first study in which the LF and FRVF are applied for the extraction of the modal parameters in aeronautically relevant structures. In addition, a novel damage detection benchmark of a high-aspect-ratio wing is introduced.

Description

Software Description

Software Language

Github

Keywords

Modal analysis, Ground vibration testing, Modal parameters, Loewner framework, Fast relaxed vector fitting, Frequency domain, Noise, Damage detection, Structural health monitoring, Aeronautical structures, Aerospace structures, High aspect ratio wings, 46 Information and Computing Sciences, 40 Engineering, 4001 Aerospace Engineering, 4001 Aerospace engineering, 4017 Mechanical engineering

DOI

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Attribution 4.0 International

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Funder/s

This work was supported by the Engineering and Physical Sciences Research Council (EPSRC) (grant number 2277626).