Unsupervised detection of faults in industrial pumps from multivariate time series
Unplanned pump failures in asset-intensive industries like pulp and paper lead to significant production losses. Data-driven predictive maintenance through anomaly detection has recently appeared to be useful in industrial settings. However, this approach is hampered by the infeasibility of manually...
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| Hlavní autoři: | , , |
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| Médium: | Artigo |
| Jazyk: | Inglês |
| Vydáno: |
Elsevier
2025-12-01
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| Edice: | Machine Learning with Applications |
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| On-line přístup: | http://www.sciencedirect.com/science/article/pii/S2666827025001677 |
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