A Symbolic Regression Based Residual Useful Life Model for Slewing Bearings. - Peng Ding 002; Qinrong Qian; Hua Wang; Jianyong Yao (IEEE Access, 2019)

Intelligent health evaluation of rolling bearings based on subspace meta-learning. - Peng Ding 002; Minping Jia (INDIN, 2020)

Fault Diagnosis of Rolling-Element Bearing Using Multiscale Pattern Gradient Spectrum Entropy Coupled with Laplacian Score. - Xiaoan Yan; Ying Liu; Peng Ding 002; Minping Jia (Complex., 2020)

Life prediction of slewing bearing based on isometric mapping and fuzzy support vector regression. - Weigang Bao; Hua Wang; Jie Chen; Bo Zhang; Peng Ding 002; Jie Wu; Peiyu He (Trans. Inst. Meas. Control, 2020)

Meta deep learning based rotating machinery health prognostics toward few-shot prognostics. - Peng Ding 002; Minping Jia; Xiaoli Zhao (Appl. Soft Comput., 2021)

Temporal convolution-based transferable cross-domain adaptation approach for remaining useful life estimation under variable failure behaviors. - Jichao Zhuang; Minping Jia; Yifei Ding; Peng Ding 002 (Reliab. Eng. Syst. Saf., 2021)

A Novel Remaining Useful Life Prediction Method of Rolling Bearings Based on Deep Transfer Auto-Encoder. - Yifei Ding; Peng Ding 002; Minping Jia (IEEE Trans. Instrum. Meas., 2021)

Statistical Alignment-Based Metagated Recurrent Unit for Cross-Domain Machinery Degradation Trend Prognostics Using Limited Data. - Peng Ding 002; Minping Jia; Yifei Ding; Xiaoli Zhao (IEEE Trans. Instrum. Meas., 2021)

Intelligent machinery health prognostics under variable operation conditions with limited and variable-length data. - Peng Ding 002; Minping Jia; Yifei Ding; Yudong Cao; Xiaoli Zhao (Adv. Eng. Informatics, 2022)

Deep imbalanced regression using cost-sensitive learning and deep feature transfer for bearing remaining useful life estimation. - Yifei Ding; Minping Jia; Jichao Zhuang; Peng Ding 002 (Appl. Soft Comput., 2022)

Self-supervised pretraining via contrast learning for intelligent incipient fault detection of bearings. - Yifei Ding; Jichao Zhuang; Peng Ding 002; Minping Jia (Reliab. Eng. Syst. Saf., 2022)

Mechatronics Equipment Performance Degradation Assessment Using Limited and Unlabeled Data. - Peng Ding 002; Minping Jia (IEEE Trans. Ind. Informatics, 2022)

Multiobjective Evolution Enhanced Collaborative Health Monitoring and Prognostics: A Case Study of Bearing Life Test With Three-Axis Acceleration Signals. - Peng Ding 002; Minping Jia; Jichao Zhuang; Yifei Ding; Yudong Cao; Xiaoli Zhao; Chi-Guhn Lee (IEEE Trans. Instrum. Meas., 2022)

Domain generalization via adversarial out-domain augmentation for remaining useful life prediction of bearings under unseen conditions. - Yifei Ding; Minping Jia; Yudong Cao; Peng Ding 002; Xiaoli Zhao; Chi-Guhn Lee (Knowl. Based Syst., 2023)

Intelligent Health Assessment of Aviation Bearing Based on Deep Transfer Graph Convolutional Networks under Large Speed Fluctuations. - Xiaoli Zhao; Xingjun Zhu; Jianyong Yao; Wenxiang Deng; Yudong Cao; Peng Ding 002; Minping Jia; Haidong Shao (Sensors, 2023)

Multiscale Deep Graph Convolutional Networks for Intelligent Fault Diagnosis of Rotor-Bearing System Under Fluctuating Working Conditions. - Xiaoli Zhao; Jianyong Yao; Wenxiang Deng; Peng Ding 002; Jichao Zhuang; Zheng Liu 002 (IEEE Trans. Ind. Informatics, 2023)

Incremental Learning for Remaining Useful Life Prediction via Temporal Cascade Broad Learning System With Newly Acquired Data. - Yudong Cao; Minping Jia; Peng Ding 002; Xiaoli Zhao; Yifei Ding (IEEE Trans. Ind. Informatics, 2023)

Intelligent Fault Diagnosis of Gearbox Under Variable Working Conditions With Adaptive Intraclass and Interclass Convolutional Neural Network. - Xiaoli Zhao; Jianyong Yao; Wenxiang Deng; Peng Ding 002; Yifei Ding; Minping Jia; Zheng Liu 002 (IEEE Trans. Neural Networks Learn. Syst., 2023)

Machinery cross domain degradation prognostics considering compound domain shifts. - Peng Ding 002; Xiaoli Zhao; Haidong Shao; Minping Jia (Reliab. Eng. Syst. Saf., 2023)

Graph structure few-shot prognostics for machinery remaining useful life prediction under variable operating conditions. - Peng Ding 002; Jun Xia; Xiaoli Zhao; Minping Jia (Adv. Eng. Informatics, 2024)

Deep temporal-spectral domain adaptation for bearing fault diagnosis. - Yifei Ding; Yudong Cao; Minping Jia; Peng Ding 002; Xiaoli Zhao; Chi-Guhn Lee (Knowl. Based Syst., 2024)

Source-free domain adaptation for transferable remaining useful life prediction of machine considering source data absence. - Yudong Cao; Jichao Zhuang; Qiuhua Miao; Minping Jia; Ke Feng; Xiaoli Zhao; Xiaoan Yan; Peng Ding 002 (Reliab. Eng. Syst. Saf., 2024)

A novel transformer-based few-shot learning method for intelligent fault diagnosis with noisy labels under varying working conditions. - Haoyu Wang; Chuanjiang Li; Peng Ding 002; Shaobo Li; Tandong Li; Chenyu Liu; Xiangjie Zhang; Zejian Hong (Reliab. Eng. Syst. Saf., 2024)

Two-Distribution Approximate Evaluation of Multiwavelet Cascade Feature Method for Noise Unbalanced Bearing Fault Diagnosis. - Xiaodong Miao; Zheng Liu 002; Kun Xu; Hua Wang; Xun Zhao; Peng Ding 002 (IEEE Trans. Instrum. Meas., 2025)

A New Intelligent Recognition Method for Surface Electromyography in IoT Systems Using OmniXceptionDBN. - Xiaoli Zhao; Yibo Song; Yuanhao Hu; Xiansong He; Zhan Zhang; Jian Hu; Jianyong Yao; Peng Ding 002; Ke Feng (IEEE Internet Things J., 2025)