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

TL;DR

Operational Modal Analysis (OMA) often struggles with noise and stability under real-world conditions. The authors propose NExT-LF, which pairs the Natural Excitation Technique (NExT) for extracting output-only impulse responses with the Loewner Framework (LF) for robust modal parameter estimation. Numerical and experimental validations demonstrate that NExT-LF achieves high accuracy and noise resilience, matching analytical results on a cantilever beam and identifying five stable modes in a real building while reducing spurious detections compared to NExT-ERA. The approach offers a scalable, efficient tool for output-only modal identification with applications in structural health monitoring and aerospace modal testing, with future work on closely spaced modes.

Abstract

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.

Figures (8)

• Figure 1: Numerical case study: 3D Euler Bernoulli beam numerical system.
• Figure 2: Numerical case study: FRF of the numerical system.
• Figure 3: Numerical ($\zeta_n=$ 1%) case study: Effects of input-output noise on the NExT-LF (top row), NExT-ERA (middle row), and SSI (bottom row) identifications (difference w.r.t analytical results) of $\omega_n$ (\ref{['fig:1ab', 'fig:1db', 'fig:1gb']}), $\zeta_n$ (\ref{['fig:1bb', 'fig:1eb', 'fig:1hb']}), and $\bm{\phi}_n$ -- in terms of MAC Value (\ref{['fig:1cb', 'fig:1fb', 'fig:1ib']}).
• Figure 4: Numerical ($\zeta_n=$ 3%) case study: Effects of input-output noise on the NExT-LF identification (difference w.r.t analytical results) of $\omega_n$ (\ref{['fig:1a']}), $\zeta_n$ (\ref{['fig:1b']}), and $\bm{\phi}_n$ -- in terms of MAC Value (\ref{['fig:1c']}).
• Figure 5: Experimental case study: Sheraton Universal Hotel -- Universal City, North Hollywood, California (USA) -- in 1987. Location coordinates: 34°08'12.0"N 118°21'36.3"W. Reproduced (Adapted) under terms of the CC-BY license.$^{\text{REF No. Not Available}}$ Copyright 2016, The Authors, published by https://www.flickr.com/photos/alan-light/25135256664/in/photostream/