A Network‐Based Approach to Identifying Key Components in Structural Vibrations

ABSTRACT Modeling the dynamics of systems with many interacting components, such as robots, wind turbines, and trusses, remains challenging today. These systems often display complex oscillatory responses to external inputs, and harmful vibrations might be excited along with the desired motion. Understanding the relative importance of individual components or systems aspects to the overall system dynamics could be a vital step towards focused design and maintenance efforts. This work proposes a network‐based approach to studying the dynamics of a mechanical system by representing the system as a network of coupled oscillators, where each node corresponds to a machine component and each link denotes a physical connection, such as a weld or bolt. Inspired by studies of dynamics in biological and social networks, we show how network measures can be used to predict the importance of a single oscillator, or component, for shaping the overall dynamics. We further demonstrate under which conditions these conclusions are possible, and where the metrics fail. This study hopes to contribute to the broader field of network‐based methods in engineering and yield insights that help focus design and maintenance efforts in the future.

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Publication Details

Journal
PAMM
Published
2025-12-01
DOI
https://doi.org/10.1002/pamm.70048
Primary Topic
Nonlinear Dynamics and Pattern Formation
Type
article
Field-Weighted Citation Impact
0.00

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article

A Network‐Based Approach to Identifying Key Components in Structural Vibrations

Norbert Hoffmann, Charlotte Geier
PAMM
Nonlinear Dynamics and Pattern Formation
article

A Network‐Based Approach to Identifying Key Components in Structural Vibrations

Norbert Hoffmann, Charlotte Geier
article en

Abstract

ABSTRACT Modeling the dynamics of systems with many interacting components, such as robots, wind turbines, and trusses, remains challenging today. These systems often display complex oscillatory responses to external inputs, and harmful vibrations might be excited along with the desired motion. Understanding the relative importance of individual components or systems aspects to the overall system dynamics could be a vital step towards focused design and maintenance efforts. This work proposes a network‐based approach to studying the dynamics of a mechanical system by representing the system as a network of coupled oscillators, where each node corresponds to a machine component and each link denotes a physical connection, such as a weld or bolt. Inspired by studies of dynamics in biological and social networks, we show how network measures can be used to predict the importance of a single oscillator, or component, for shaping the overall dynamics. We further demonstrate under which conditions these conclusions are possible, and where the metrics fail. This study hopes to contribute to the broader field of network‐based methods in engineering and yield insights that help focus design and maintenance efforts in the future.

PAMMVol. 25(4)
Universität Hamburg (DE), NIHR Imperial Biomedical Research Centre (GB), Imperial College London (GB), Hamburg University of Technology (DE)
Deutsche Forschungsgemeinschaft
Affordable and clean energy
Openalex Percentile: Top 33%
Nonlinear Dynamics and Pattern Formation
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A Network‐Based Approach to Identifying Key Components in Structural Vibrations — Norbert Hoffmann, Charlotte Geier · PAMM (2025) | TGRS Research Map | TGRS