Optimization of Practicality for Modeling- and Machine Learning-Based Framework for Early Fault Detection of Induction Motors

Optimization of Practicality for Modeling- and Machine Learning-Based Framework for Early Fault Detection of Induction Motors

This paper addresses the further development and optimization of a modeling- and machine learning-based framework for early fault detection and diagnosis in induction motors. The goal behind the multi-level framework is to provide a pragmatic and practical approach for the autonomous monitoring of e...

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Bibliographic Details
Main Authors: Moritz Benninger, Marcus Liebschner
Format: Article
Language:English
Published: MDPI AG 2024-07-01
Series:Energies
Subjects:
fault detection
induction motors
supervised learning
machine learning
modeling
parameter identification
Online Access:https://www.mdpi.com/1996-1073/17/15/3723

Internet

https://www.mdpi.com/1996-1073/17/15/3723

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