Few-Shot Lightweight SqueezeNet Architecture for Induction Motor Fault Diagnosis Using Limited Thermal Image Dataset

Few-Shot Lightweight SqueezeNet Architecture for Induction Motor Fault Diagnosis Using Limited Thermal Image Dataset

In the realm of renewable energy, wind turbines play a pivotal role in efficiently harnessing wind power, especially in offshore environments, where their significance is amplified. These turbines require vigilant monitoring due to the elevated risk of operational faults. Moreover, vast labeled data...

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Bibliographic Details
Main Authors: Farhan Md. Siraj, Syed Tasnimul Karim Ayon, Md. Abdus Samad, Jia Uddin, Kwonhue Choi
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Few-shot learning
fault diagnosis
deep learning
limited data
prototypical network
induction generator
Online Access:https://ieeexplore.ieee.org/document/10493002/

Internet

https://ieeexplore.ieee.org/document/10493002/

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