Non-negative tensor factorization for vibration-based local damage detection

In this study, a novel non-negative tensor factorization (NTF)-based method for vibration-based local damage detection in rolling element bearings is proposed. As the diagnostic signal registered from a faulty machine is non-stationary, the time-frequency method is frequently used as a primary decom...

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Bibliographic Details
Published in:arXiv.org 2024-03
Main Authors: Gabor, Mateusz, Zdunek, Rafal, Zimroz, Radoslaw, Wodecki, Jacek, Wylomanska, Agnieszka
Format: Article
Language:English
Subjects:
Damage detection
Factorization
Mathematical analysis
Roller bearings
Tensors
Time-frequency analysis
Vibration
Online Access:Get full text
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Summary:In this study, a novel non-negative tensor factorization (NTF)-based method for vibration-based local damage detection in rolling element bearings is proposed. As the diagnostic signal registered from a faulty machine is non-stationary, the time-frequency method is frequently used as a primary decomposition technique. It is proposed here to extract multi-linear NTF-based components from a 3D array of time-frequency representations of an observed signal partitioned into blocks. As a result, frequency and temporal informative components can be efficiently separated from non-informative ones. The experiments performed on synthetic and real signals demonstrate the high efficiency of the proposed method with respect to the already known non-negative matrix factorization approach.
ISSN:2331-8422
DOI:10.48550/arxiv.2403.12554