An Improved Fault Diagnosis Strategy for Induction Motors Using Weighted Probability Ensemble Deep Learning

An Improved Fault Diagnosis Strategy for Induction Motors Using Weighted Probability Ensemble Deep Learning

Early detection of faults in induction motors is crucial for ensuring uninterrupted operations in industrial settings. Among the various fault types encountered in induction motors, bearing, rotor, and stator faults are the most prevalent. This paper introduces a Weighted Probability Ensemble Deep L...

Full description

Saved in:
Bibliographic Details
Main Authors: Usman Ali, Umer Ramzan, Waqas Ali, Khaled Ali Al-Jaafari
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Access
Subjects:
Induction motor
ensemble learning
deep learning
STFT images
fault diagnosis
Online Access:https://ieeexplore.ieee.org/document/11037405/
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://ieeexplore.ieee.org/document/11037405/

Similar Items