Exploring localization in nonlinear oscillator systems through network-based predictions

Fuente: arXiv
Enregistré dans:
Détails bibliographiques
Auteurs principaux: Geier, Charlotte, Hoffmann, Norbert
Format: Preprint
Publié: 2024
Sujets:
Accès en ligne:
Tags: Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
_version_ 1866918020775936000
author Geier, Charlotte
Hoffmann, Norbert
author_facet Geier, Charlotte
Hoffmann, Norbert
contents Localized vibrations, arising from nonlinearities or symmetry breaking, pose a challenge in engineering, as the resulting high-amplitude vibrations may result in component failure due to fatigue. During operation, the emergence of localization is difficult to predict, partly because of changing parameters over the life cycle of a system. This work proposes a novel, network-based approach to detect an imminent localized vibration. Synthetic measurement data is used to generate a functional network, which captures the dynamic interplay of the machine parts, complementary to their geometric coupling. Analysis of these functional networks reveals an impending localized vibration and its location. The method is demonstrated using a model system for a bladed disk, a ring composed of coupled nonlinear Duffing oscillators. Results indicate that the proposed method is robust against small parameter uncertainties, added measurement noise, and the length of the measurement data samples. The source code for this work is available.
format Preprint
id arxiv_https___arxiv_org_abs_2407_05497
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Exploring localization in nonlinear oscillator systems through network-based predictions
Geier, Charlotte
Hoffmann, Norbert
Dynamical Systems
Adaptation and Self-Organizing Systems
Localized vibrations, arising from nonlinearities or symmetry breaking, pose a challenge in engineering, as the resulting high-amplitude vibrations may result in component failure due to fatigue. During operation, the emergence of localization is difficult to predict, partly because of changing parameters over the life cycle of a system. This work proposes a novel, network-based approach to detect an imminent localized vibration. Synthetic measurement data is used to generate a functional network, which captures the dynamic interplay of the machine parts, complementary to their geometric coupling. Analysis of these functional networks reveals an impending localized vibration and its location. The method is demonstrated using a model system for a bladed disk, a ring composed of coupled nonlinear Duffing oscillators. Results indicate that the proposed method is robust against small parameter uncertainties, added measurement noise, and the length of the measurement data samples. The source code for this work is available.
title Exploring localization in nonlinear oscillator systems through network-based predictions
topic Dynamical Systems
Adaptation and Self-Organizing Systems
url https://arxiv.org/abs/2407.05497