arXiv subjects

Gabriele Dessena

Publications and source records attributed to Gabriele Dessena.

10 recordsLinked to original sources

arXiv2026

International Space Station operational modal analysis via iterative pole relocation

In recent years, increasing aerospace safety requirements have intensified the demand for reliable structural damage detection. This work presents an Operational Modal Analysis approach for accurate modal parameter estimation, with an application to space structure monitoring. The proposed System Identification (SI) method innovatively combines the Natural Excitation Technique (NExT) with the Fast and Relaxed Vector Fitting (FRVF) algorithm, which uses an iterative least-squares optimisation. A preliminary validation is first carried out on a numerical beam model, comparing results with analytical solutions and the established Natural Excitation Technique with Eigensystem Realisation Algorithm (NExT-ERA) and Stochastic Subspace Identification with Canonical Variate Analysis (SSI) methods. Then, operational validation is performed on real acceleration data from the Space Acceleration Measurement Systems aboard the International Space Station. Identified vibration modes from NExT-FRVF and NExT-ERA show comparable results after signal processing, with mode consistency assessed by repeated occurrence and physical interpretation, while SSI fails to identify most. The output-only algorithm proves to be highly reliable, outperforming benchmark methods under noisy conditions on a numerical system and offering reliable identifications on the experimental data.

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arXiv2026

Enhanced input stacking for non-square MIMO modal identification of aeronautical structures via Fast and Relaxed Vector Fitting

Fast and Relaxed Vector Fitting (FRVF) is a frequency-domain system identification approach that has been widely adopted in electrical system modelling, while its application to mechanical systems has remained relatively unexplored. In this work, FRVF is reformulated for the identification of structural modal parameters of an aircraft based on Ground Vibration Test (GVT) data within a Multi-Input Multi-Output (MIMO) framework. The proposed procedure consists of three stages: (i) rational approximation of frequency response functions via an enhanced input-stacking strategy, (ii) identification of system poles from the resulting rational model, and (iii) estimation of modal parameters from the extracted poles and associated residues. The methodology is first numerically validated on a MIMO beam model, with particular emphasis on accuracy and robustness under increasing measurement noise. Subsequently, experimental validation is conducted using GVT data from the BAE Systems Hawk T1A aircraft. The results obtained demonstrate a level of performance comparable to that achieved by existing methods. Overall, the extended MIMO formulation of FRVF exhibits high accuracy and strong robustness to measurement noise, highlighting its suitability for application in GVT-based modal analysis.

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arXiv2026

Operational Modal Analysis of Aeronautical Structures via Tangential Interpolation

Over the last decades, progress in modal analysis has enabled increasingly routine use of modal parameters for applications such as structural health monitoring and finite element model updating. For output-only identification, or Operational Modal Analysis (OMA), widely adopted approaches include Stochastic Subspace Identification (SSI) methods and the Natural Excitation Technique combined with the Eigensystem Realization Algorithm (NExT-ERA). Nevertheless, SSI-based techniques may become cumbersome on large systems, while NExT-ERA fitting can struggle when measurements are contaminated by noise. To alleviate these, this work investigates an OMA frequency-domain formulation for aeronautical structures by coupling the Loewner Framework (LF) with NExT, yielding the proposed NExT-LF method. The method exploits the computational efficiency of LF, due to the effectiveness of tangential interpolation, together with the impulse response function retrieval enabled by NExT. NExT-LF is assessed on two experimental benchmarks: the eXperimental BeaRDS 2 high-aspect-ratio wing main spar and an Airbus Helicopters H135 bearingless main rotor blade. The identified modal parameters are compared against available experimental references and results obtained via SSI with Canonical Variate Analysis and NExT-ERA. The results show that the modes identified by NExT-LF correlate well with benchmark data, particularly for high-amplitude tests and in the low-frequency range.

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arXiv2026

Modal Parameter Extraction via Propeller-Driven Vibration Testing

Ground Vibration Testing (GVT) supports aircraft certification but often requires lengthy and costly campaigns. Propeller-driven Vibration Testing (PVT) is assessed here as an output-only alternative, in line with Operational Modal Analysis approaches such as Taxi Vibration Testing and Flight Vibration Testing. A cantilever Aluminium 7075-T6 wing spar is instrumented with seven accelerometers and excited by an outboard electric motor and propeller. Seven runs are carried out: a motor-off baseline, five constant-throttle cases, and a manual up-down throttle sweep. The acquired spectra indicate that the dominant resonances remain observable under propeller excitation, while low-throttle conditions introduce narrowband harmonics that may mask structural peaks; the sweep reduces persistent overlap. Modal parameters are identified for the baseline and sweep cases using the Natural Excitation Technique with the Loewner Framework (NExT-LF). The first two modes remain closely matched (Modal Assurance Criterion (MAC) > 0.99), whereas the third mode shows reduced repeatability (MAC = 0.827) and a larger frequency shift, consistent with propeller-induced bending--torsion coupling and non-ideal sweep control. Overall, PVT provides a viable complement to GVT for extracting low-frequency modal information and motivates pursuing future work on automated throttle scheduling and coupling-aware test planning.

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arXiv2026

Affordable Data Collection System for UAVs Taxi Vibration Testing

Structural vibration testing plays a key role in aerospace engineering for evaluating dynamic behaviour, ensuring reliability and verifying structural integrity. These tests rely on accurate and robust data acquisition systems (DAQ) to capture high-quality acceleration data. However, commercial DAQs that provide the required performance and features are often expensive and complex, limiting their accessibility for small-scale research and experimental applications. This work presents the design and experimental validation of an affordable and in-house-developed acceleration DAQ, tested on a small fixed-wing UAV through several Taxi Vibration Test (TVT) runs and ambient vibration measurements. The proposed system integrates several OrangePi 3 LTS single-board computers with multiple LSM6DS3TR-C MEMS inertial measurement units operating simultaneously via an Inter-Integrated Circuit (I2C) communication interface, managed under a Python-based master/slave architecture. Data is acquired at a stable sampling rate of approximately 208 Hz and post-processed using Welch's method to estimate their Power Spectral Density (PSD). Results confirm the system ability to provide consistent multi-sensor acceleration data and repeatable PSD profiles under the same test conditions; thus, demonstrating its reliability. With a total hardware cost below 600 EUR (approximately 690 USD), the developed DAQ offers a compact, scalable and cost-effective alternative for aerospace vibration analysis and structural testing.

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arXiv2025

Damping Identification Sensitivity in Flutter Speed Estimation

Predicting flutter remains a key challenge in aeroelastic research, with certain models relying on modal parameters, such as natural frequencies and damping ratios. These models are particularly useful in early design stages or for the development of small Unmanned Aerial Vehicles (maximum take-off mass below 7 kg). This study evaluates two frequency-domain system identification methods, Fast Relaxed Vector Fitting (FRVF) and the Loewner Framework (LF), for predicting the flutter onset speed of a flexible wing model. Both methods are applied to extract modal parameters from Ground Vibration Testing data, which are subsequently used to develop a reduced-order model with two degrees of freedom. Results indicate that FRVF and LF-informed models provide reliable flutter speed, with predictions deviating by no more than 3% (FRVF) and 5% (LF) from the N4SID-informed benchmark. The findings highlight the sensitivity of flutter speed predictions to damping ratio identification accuracy and demonstrate the potential of these methods as computationally efficient alternatives for preliminary aeroelastic assessments.

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arXiv2024

A Paradigm Shift to Assembly-like Finite Element Model Updating

In general, there is a mismatch between a finite element model {(FEM)} of a structure and its real behaviour. In aeronautics, this mismatch must be small because {FEM}s are a fundamental part of the development of an aircraft and of increasing importance with the trend to more flexible wings in modern designs. Iterative finite element model updating can be computationally expensive for complex structures, and surrogate models can be employed to reduce the computational burden. A novel approach for FEM updating, namely assembly-like, is proposed and validated using real experimental data from a flexible wing. The assembly-like model updating framework implies that the model is updated as parts are assembled. Benchmarking against the classical global, or one-shot, approach demonstrates that the proposed method is more computationally efficient, since a normalised workload proxy based on solver-reported model size and memory footprint indicates about 28\% lower overall effort. Aapproximately 95\% of the required solves are performed on lower-fidelity subassembly models with smaller equation counts and memory requirements. Despite the reduced reliance on full-wing evaluations, the new approach retains the fidelity, within 1\% of a joint natural frequencies and modal shapes index, of the global approach.

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arXiv2024

NExT-LF: A Novel Operational Modal Analysis Method via Tangential Interpolation

Operational Modal Analysis (OMA) is vital for identifying modal parameters under real-world conditions, yet existing methods often face challenges with noise sensitivity and stability. This work introduces NExT-LF, a novel method that combines the well-known Natural Excitation Technique (NExT) with the Loewner Framework (LF). NExT enables the extraction of Impulse Response Functions (IRFs) from output-only vibration data, which are then converted into the frequency domain and used by LF to estimate modal parameters. The proposed method is validated through numerical and experimental case studies. In the numerical study of a 2D Euler-Bernoulli cantilever beam, NExT-LF provides results consistent with analytical solutions and those from standard methods, NExT with Eigensystem Realization Algorithm (NExT-ERA) and Stochastic Subspace Identification with Canonical Variate Analysis (SSI). Additionally, NExT-LF demonstrates superior noise robustness, reliably identifying stable modes across various noise levels where NExT-ERA fails. Experimental validation on the Sheraton Universal Hotel is the first OMA application to this structure, confirming NExT-LF as a robust and efficient method for output-only modal parameter identification.

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arXiv2024

Multiple input tangential interpolation-driven damage detection of a jet trainer aircraft

The problem of damage detection and identification is of interest for many aerospace and aeronautical engineering systems. However, relevant literature mostly focuses on subsystems and parts, rather than full airframes. In structural dynamics, modal parameters, such as natural frequencies and mode shapes, from any structure are the main building blocks of vibration-based damage detection. However, traditional comparisons of these parameters are often ambiguous in complex systems, complicating damage detection and assessment. The modified total modal assurance criterion (MTMAC), an index well-known in the field of finite element model updating, is extended to address this challenge and is proposed as an index for damage identification and severity assessment. To support the requirement for precise and robust modal identification of Structural Health Monitoring (SHM), the improved Loewner Framework (iLF), known for its reliability and computational performance, is pioneeringly employed within SHM. Since the MTMAC is proposed solely as a damage identification and severity assessment index, the coordinate modal assurance criterion (COMAC), also a well-established tool, but for damage localisation using mode shapes, is used for completeness. The iLF SHM capabilities are validated through comparisons with traditional methods, including least-squares complex exponential and stochastic subspace identification with canonical variate analysis on a numerical case study of a cantilever beam. Furthermore, the MTMAC is validated against the traditional vibration-based approach, which involves directly comparing natural frequencies and mode shapes. Finally, an experimental dataset from a BAE Systems Hawk T1A jet trainer ground vibration test is used to demonstrate the iLF and MTMAC capabilities on a real-life, real-size SHM problem, showing their effectiveness in detecting and assessing damage.

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arXiv2024

Improved Tangential Interpolation-based Multi-input Multi-output Modal Analysis of a Full Aircraft

In the field of Structural Dynamics, modal analysis is the foundation of System Identification and vibration-based inspection. However, despite their widespread use, current state-of-the-art methods for extracting modal parameters from multi-input multi-output (MIMO) frequency domain data are still affected by many technical limitations. Mainly, they can be computationally cumbersome and/or negatively affected by close-in-frequency modes. The Loewner Framework (LF) was recently proposed to alleviate these problems with the limitation of working with single-input data only. This work proposes a computationally improved version of the LF, or iLF, to extract modal parameters more efficiently. Also, the proposed implementation is extended in order to handle MIMO data in the frequency domain. This new implementation is compared to state-of-the-art methods such as the frequency domain implementations of the Least Square Complex Exponential method and the Numerical Algorithm for Subspace State Space System Identification on numerical and experimental datasets. More specifically, a finite element model of a 3D Euler-Bernoulli beam is used for the baseline comparison and the noise robustness verification of the proposed MIMO iLF algorithm. Then, an experimental dataset from MIMO ground vibration tests of a trainer jet aircraft with over 91 accelerometer channels is chosen for the algorithm validation on a real-life application. Its validation is carried out with known results from a single-input multi-output dataset of the starboard wing of the same aircraft. Excellent results are achieved in terms of accuracy, robustness to noise, and computational performance by the proposed improved MIMO method, both on the numerical and the experimental datasets. The MIMO iLF MATLAB implementation is shared in the work supplementary material.

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