A Fusing Domain Feature and Sharing Label Space-Based Fault Diagnosis Approach for Different Distribution and Unlabeled Rolling Bearing Sample. - Xuejun Liu; Wei Sun 030; Hongkun Li; Qiang Li; Shuai Lv 004 (IEEE Trans. Instrum. Meas., 2023)

A hybrid method combining Lévy process and neural network for predicting remaining useful life of rotating machinery. - Shuai Lv 004; Shujie Liu 003; Hongkun Li; Yu Wang 113; Gengshuo Liu; Wei Dai (Adv. Eng. Informatics, 2024)

A first-order meta learning method for remaining useful life prediction of rotating machinery under limited samples. - Yu Wang 113; Shujie Liu 003; Shuai Lv 004; Gengshuo Liu (Appl. Soft Comput., 2025)

New Method for Remaining Useful Life Prediction Based on Recurrence Multi-Information Time-Frequency Transformer Networks: RUL Prediction with Recurrence Multi-Information TF Transformers. - Shuai Lv 004; Shujie Liu 003; Hongkun Li (Qual. Reliab. Eng. Int., 2025)

A novel method for predicting the remaining useful life of MOSFETs based on a linear multi-fractional Lévy stable motion driven by a GRU similarity transfer network. - Shuai Lv 004; Shujie Liu 003; Hongkun Li; Yu Wang 113; Gengshuo Liu; Wei Dai (Reliab. Eng. Syst. Saf., 2025)

Meta-Learning and Knowledge Discovery based Physics-Informed Neural Network for Remaining Useful Life Prediction. - Yu Wang 113; Shujie Liu 003; Shuai Lv 004; Gengshuo Liu (CoRR, 2025)