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

TL;DR

This paper adapts the Fast and Relaxed Vector Fitting method for aircraft structural modal identification using Ground Vibration Test data, emphasizing enhanced input stacking for improved accuracy and robustness.

Contribution

It introduces an extended MIMO formulation of FRVF with an enhanced input-stacking strategy for better modal parameter estimation in aeronautical structures.

Findings

Numerical validation shows high accuracy under noise.

Experimental results on aircraft data demonstrate robustness.

Method performs comparably to existing approaches.

Abstract

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.