Fault diagnosis of rotary machinery components using a stacked denoising autoencoder-based health state identification. - Chen Lu 001; Zhenya Wang; Wei-Li Qin; Jian Ma 006 (Signal Process., 2017)

Fault Diagnosis of Electromechanical Actuator Based on VMD Multifractal Detrended Fluctuation Analysis and PNN. - Hongmei Liu 004; Jiayao Jing; Jian Ma 006 (Complex., 2018)

Predicting the Remaining Useful Life of an Aircraft Engine Using a Stacked Sparse Autoencoder with Multilayer Self-Learning. - Jian Ma 006; Hua Su; Wan-lin Zhao; Bin Liu 032 (Complex., 2018)

A Generative Adversarial Network-Based Intelligent Fault Diagnosis Method for Rotating Machinery Under Small Sample Size Conditions. - Yu Ding 003; Liang Ma; Jian Ma 006; Chao Wang; Chen Lu 001 (IEEE Access, 2019)

Intelligent fault diagnosis for rotating machinery using deep Q-network based health state classification: A deep reinforcement learning approach. - Yu Ding 003; Liang Ma; Jian Ma 006; Mingliang Suo; Laifa Tao; Yujie Cheng; Chen Lu 001 (Adv. Eng. Informatics, 2019)

State-of-Health Prediction for Reaction Wheel of On-Orbit Satellite Based on Fourier Broad Learning System. - Xingliu Zhang; Zili Wang 002; Jian Ma 006; Shangyu Li; Mingliang Suo (IEEE Access, 2021)

An interpretable data augmentation scheme for machine fault diagnosis based on a sparsity-constrained generative adversarial network. - Liang Ma; Yu Ding 003; Zili Wang 002; Chao Wang; Jian Ma 006; Chen Lu 001 (Expert Syst. Appl., 2021)

A novel Long-term degradation trends predicting method for Multi-Formulation Li-ion batteries based on deep reinforcement learning. - Chao Wang; Yu Ding 003; Ning Yan; Liang Ma; Jian Ma 006; Chen Lu 001; Chao Yang; Yuzhuan Su; Jin Chong; Haizu Jin; Yongshou Lin (Adv. Eng. Informatics, 2022)

An adversarial model for electromechanical actuator fault diagnosis under nonideal data conditions. - Chao Wang; Laifa Tao; Yu Ding 003; Chen Lu 001; Jian Ma 006 (Neural Comput. Appl., 2022)

A prediction-based cycle life test optimization method for cross-formula batteries using instance transfer and variable-length-input deep learning model. - Jian Ma 006; XinYu Zou; Lulu Sun; Yujie Cheng; Chen Lu 001; Yuzhuan Su; Jin Chong; Haizu Jin; Yongshou Lin (Neural Comput. Appl., 2023)

A case-learning-based paradigm for quantitative recommendation of fault diagnosis algorithms: A case study of gearbox. - XinYu Zou; Laifa Tao; Lulu Sun; Chao Wang; Jian Ma 006; Chen Lu 001 (Reliab. Eng. Syst. Saf., 2023)

An adaptive fault diagnosis framework under class-imbalanced conditions based on contrastive augmented deep reinforcement learning. - Qin Zhao; Yu Ding 003; Chen Lu 001; Chao Wang; Liang Ma; Laifa Tao; Jian Ma 006 (Expert Syst. Appl., 2023)

An Outline of Prognostics and Health Management Large Model: Concepts, Paradigms, and Challenges. - Laifa Tao; Shangyu Li; Haifei Liu; Qixuan Huang; Liang Ma; Guoao Ning; Yiling Chen; Yunlong Wu; Bin Li; Weiwei Zhang; Zhengduo Zhao; Wenchao Zhan; et al. (CoRR, 2024)

A rail defect detection framework under class-imbalanced conditions based on improved you only look once network. - Yu Ding 003; Qin Zhao; Tianhao Li; Chen Lu 001; Laifa Tao; Jian Ma 006 (Eng. Appl. Artif. Intell., 2024)

Remaining useful life prediction and cycle life test optimization for multiple-formula battery: A method based on multi-source transfer learning. - Dengwei Song; Yujie Cheng; An Zhou; Chen Lu 001; Jin Chong; Jian Ma 006 (Reliab. Eng. Syst. Saf., 2024)

Open-Set Fault Recognition and Inference for Rolling Bearing Based on Open Fault Semantic Subspace. - Yu Chen; Laifa Tao; Xue Liu; Jian Ma 006; Chen Lu 001; Hongmei Liu 004 (IEEE Trans. Instrum. Meas., 2024)

Quantitative recommendation of fault diagnosis algorithms based on multi-order random graph convolution under case-learning paradigm. - Chen Lu 001; XinYu Zou; Lulu Sun; Zhengduo Zhao; Laifa Tao; Yu Ding 003; Jian Ma 006 (Adv. Eng. Informatics, 2025)