A Regularized LSTM Method for Predicting Remaining Useful Life of Rolling Bearings. - Zhao-Hua Liu; Xudong Meng; Hua-Liang Wei; Liang Chen; Bi-Liang Lu; Zhenheng Wang; Lei Chen 045 (Int. J. Autom. Comput., 2021)

A Deep Adversarial Learning Prognostics Model for Remaining Useful Life Prediction of Rolling Bearing. - Bi-Liang Lu; Zhao-Hua Liu; Hua-Liang Wei; Lei Chen 045; Hongqiang Zhang; Xiao-Hua Li (IEEE Trans. Artif. Intell., 2021)

A Stacked Auto-Encoder Based Partial Adversarial Domain Adaptation Model for Intelligent Fault Diagnosis of Rotating Machines. - Zhao-Hua Liu; Bi-Liang Lu; Hua-Liang Wei; Lei Chen 045; Xiao-Hua Li; Chang-Tong Wang (IEEE Trans. Ind. Informatics, 2021)

Deep Adversarial Domain Adaptation Model for Bearing Fault Diagnosis. - Zhao-Hua Liu; Bi-Liang Lu; Hua-Liang Wei; Lei Chen 045; Xiao-Hua Li; Matthias Rätsch (IEEE Trans. Syst. Man Cybern. Syst., 2021)

Flow Measurement-Based Self-Adaptive Line Segment Clustering Model for Leakage Detection in Water Distribution Networks. - Qingshuai Sun; Yingjie Zhang; Bi-Liang Lu; Hualiang Liu (IEEE Trans. Instrum. Meas., 2022)

An Enhanced Adaptive Unscented Kalman Filter for Vehicle State Estimation. - Yingjie Zhang; Ming Li; Ying Zhang; Zuolei Hu; Qingshuai Sun; Bi-Liang Lu (IEEE Trans. Instrum. Meas., 2022)

A novel sample selection approach based universal unsupervised domain adaptation for fault diagnosis of rotating machinery. - Bi-Liang Lu; Yingjie Zhang; Zhaohua Liu; Hua-Liang Wei; Qingshuai Sun (Reliab. Eng. Syst. Saf., 2023)

A Novel Multidomain Contrastive-Coding-Based Open-Set Domain Generalization Framework for Machinery Fault Diagnosis. - Bi-Liang Lu; Yingjie Zhang; Qingshuai Sun; Ming Li; Pude Li (IEEE Trans. Ind. Informatics, 2024)