FreqMGCN-Net: An IoT-Integrated Multi-Parallel Graph Convolutional Network with frequency attention for motor bearing fault diagnosis

FreqMGCN-Net: An IoT-Integrated Multi-Parallel Graph Convolutional Network with frequency attention for motor bearing fault diagnosis

Motor bearing fault diagnosis is crucial for predictive maintenance in industrial systems. Traditional methods struggle with complex vibration signals, especially under noisy conditions and with limited labeled data. The advent of Internet of Things (IoT) technology enables real-time data collection...

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Bibliographic Details
Main Authors: Jicai Wang, Shahrum Abdullah, Chen Gao, Azli Arifin, Salvinder Singh Karam Sing
Format: Article
Language:English
Published: Elsevier 2025-09-01
Series:Alexandria Engineering Journal
Subjects:
Motor bearing fault diagnosis
Frequency attention mechanism
Multi-parallel graph convolutional networks
Semi-supervised meta-learning
Few-shot learning
IOT
Online Access:http://www.sciencedirect.com/science/article/pii/S1110016825006398
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