Improved Diagnostic Approach for BRB Detection and Classification in Inverter-Driven Induction Motors Employing Sparse Stacked Autoencoder (SSAE) and LightGBM

This study introduces an innovative approach to diagnostics, employing a unique combination of techniques including a stratified group K-fold cross-validation method and a sparse stacked autoencoder (SSAE) alongside LightGBM. By examining signatures derived from motor current, voltage, speed, and to...

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Bibliographic Details
Published in:Electronics (Basel) Vol. 13; no. 7; p. 1292
Main Authors: Khan, Muhammad Amir, Asad, Bilal, Vaimann, Toomas, Kallaste, Ants
Format: Journal Article
Language:English
Published: Basel MDPI AG 01.04.2024
Subjects:
Algorithms
Classification
Datasets
Defects
Diagnostic systems
Evaluation
Fault diagnosis
Feature extraction
Induction electric motors
Induction motors
Inverters
Labels
Machine learning
Machinery
Magneto-electric machines
Methods
Neural networks
Sensors
Signatures
ISSN:2079-9292, 2079-9292
Online Access:Get full text
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