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

• Published in: IEEE transactions on instrumentation and measurement Vol. 71; p. 1
• Main Authors: Lyu, Pin, Zheng, Pai, Yu, Wenbing, Liu, Chao, Xia, Min
• Format: Journal Article
• Language: English
• Published: New York IEEE 2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: 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

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...