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

TL;DR

NExT-LF is a new operational modal analysis method that combines NExT and Loewner Framework to improve noise robustness and stability in identifying modal parameters from output-only vibration data, validated through numerical and experimental studies.

Contribution

This paper introduces NExT-LF, a novel OMA method that integrates NExT with the Loewner Framework, enhancing noise robustness and stability over existing techniques.

Findings

NExT-LF yields results consistent with analytical solutions and standard methods.

It demonstrates superior noise robustness compared to NExT-ERA.

Validated on both numerical models and real-world structures.

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.