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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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Principais autores: Jungyu Choi, Sungbin Im
Format: Artigo
Sprog:Inglês
Udgivet: IEEE 2024-01-01
Serier:IEEE Access
Fag:
Anomaly detection
unsupervised learning
frequency distortion
damage detection
multivariate kernel density estimation
three-phase induction motor
Online adgang:https://ieeexplore.ieee.org/document/10685346/
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