A Novel Data Augmentation Method Based on Denoising Diffusion Probabilistic Model for Fault Diagnosis Under Imbalanced Data
Authors: Xiongyan Yang; Tianyi Ye; Xianfeng Yuan; Weijie Zhu; Xiaoxue Mei; Fengyu Zhou
Abstract:
Imbalanced data present a notable challenge in intelligent fault diagnosis, as the scarcity of fault samples often results in biased learning and reduced diagnostic accuracy. Conventional approaches, such as cost-sensitive learning, resampling, and …