A Novel Multiview Sampling-based Meta Self-Paced Learning Approach for Class-imbalanced Intelligent Fault Diagnosis

In practical machine fault diagnosis, the obtained data samples under faulty conditions are usually far less than those under normal conditions, resulting in a class-imbalanced dataset issue. The existing solutions for class-imbalanced scenarios include data-level and model-level strategies which ar...

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Veröffentlicht in:	IEEE transactions on instrumentation and measurement 2022, Vol.71, p.1-1
Hauptverfasser:	Lyu, Pin, Zheng, Pai, Yu, Wenbing, Liu, Chao, Xia, Min
Format:	Artikel
Sprache:	eng
Schlagworte:	Adaptation models Artificial neural networks Biological system modeling class-imbalanced data Comparative studies Datasets Fault diagnosis Feature extraction Frequency domain analysis Generative adversarial networks Machine learning meta self-paced learning multiview sampling Performance enhancement Sampling methods self-paced learning Signal processing Support vector machines Training
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