English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Tools annual

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

We introduce an approach for damage detection in gearboxes based on theanalysis of sensor data with the multi-resolution dynamic mode decomposition(mrDMD). The application focus is the condition monitoring of wind turbinegearboxes under varying load conditions, in particular irregular and stochasticwind fluctuations. We analyze data stemming from a simulated vibration responseof a simple nonlinear gearbox model in a healthy and damaged scenario and underdifferent wind conditions. With mrDMD applied on time-delay snapshots of thesensor data, we can extract components in these vibration signals thathighlight features related to damage and enable its identification. Acomparison with Fourier analysis, Time Synchronous Averaging and Empirical ModeDecomposition shows the advantages of the proposed mrDMD-based data analysisapproach for damage detection.

Multi-resolution Dynamic Mode Decomposition for Damage Detection in Wind Turbine Gearboxes