Multivariate Kernel Density Estimation Performance in Detecting Abnormalities in Three-Phase Induction Motors With a Focus on Optimizing Kernel and Bandwidth

In this study, we focus on the application of anomaly detection for three-phase induction motors using current data, a crucial aspect of predictive maintenance technologies transforming industrial operations. Induction motors play a pivotal role in converting electrical energy to mechanical energy a...

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Váldodahkkit:	Jungyu Choi, Sungbin Im
Materiálatiipa:	Artigo
Giella:	Inglês
Almmustuhtton:	IEEE 2024-01-01
Ráidu:	IEEE Access
Fáttát:	Anomaly detection unsupervised learning frequency distortion damage detection multivariate kernel density estimation three-phase induction motor
Liŋkkat:	https://ieeexplore.ieee.org/document/10685346/
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