Non-negative tensor factorization for vibration-based local damage detection
Fuente:
arXiv
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| Auteurs principaux: | , , , , |
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866910373414699008 |
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| author | Gabor, Mateusz Zdunek, Rafal Zimroz, Radoslaw Wodecki, Jacek Wylomanska, Agnieszka |
| author_facet | Gabor, Mateusz Zdunek, Rafal Zimroz, Radoslaw Wodecki, Jacek Wylomanska, Agnieszka |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2403_12554 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Non-negative tensor factorization for vibration-based local damage detection Gabor, Mateusz Zdunek, Rafal Zimroz, Radoslaw Wodecki, Jacek Wylomanska, Agnieszka Signal Processing 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. |
| title | Non-negative tensor factorization for vibration-based local damage detection |
| topic | Signal Processing |
| url | https://arxiv.org/abs/2403.12554 |