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.
Advanced GAN architecture combining Conditional Latent Diffusion Denoising with Continuous Wavelet Transform generation for enhanced fault classification in industrial systems.