Temporal Convolutional Networks

An Efficient Approach for Synthetic Data Generation and Fault Diagnosis for Rotating Machinery

This study explores the use of an Auxiliary Classifier Wasserstein GAN with Gradient Penalty (ACWGAN-GP) for synthetic data generation and fault diagnosis in rotating machinery, addressing data scarcity and class imbalance challenges.