Class Imbalanced Fault Diagnosis via Combining K-Means Clustering Algorithm with Generative Adversarial Networks

• Published in: Journal of advanced computational intelligence and intelligent informatics Vol. 25; no. 3; pp. 346 - 355
• Main Authors: Li, Huifang, Fan, Rui, Shi, Qisong, Du, Zijian
• Format: Journal Article
• Language: English
• Published: Tokyo Fuji Technology Press Co. Ltd 01.05.2021
• Subjects: Accuracy; Algorithms; Artificial neural networks; Belief networks; Cluster analysis; Clustering; Datasets; Diagnostic systems; Fault diagnosis; Generative adversarial networks; Machine learning; Oversampling; Vector quantization
• ISSN: 1343-0130; 1883-8014
• DOI: 10.20965/jaciii.2021.p0346

Recent advancements in machine learning and communication technologies have enabled new approaches to automated fault diagnosis and detection in industrial systems. Given wide variation in occurrence frequencies of different classes of faults, the class distribution of real-world industrial fault da...