Xingqiu Li

发表

Data synthesis using deep feature enhanced generative adversarial networks for rolling bearing imbalanced fault diagnosis

Shaowei Liu, Hongkai Jiang, Zhenghong Wu, 2022 .

Intelligent fault diagnosis of rolling bearings using an improved deep recurrent neural network

Hongkai Jiang, Xingqiu Li, Haidong Shao, 2018 .

Bearing incipient fault feature extraction using adaptive period matching enhanced sparse representation

Renhe Yao, Hongkai Jiang, Xingqiu Li, 2022, Mechanical Systems and Signal Processing.

A reinforcement ensemble deep transfer learning network for rolling bearing fault diagnosis with Multi-source domains

Hongkai Jiang, Zhenghong Wu, Xingqiu Li, 2022, Adv. Eng. Informatics.

A novel method for intelligent fault diagnosis of rolling bearings using ensemble deep auto-encoders

Haidong Shao, Ying Lin, Hongkai Jiang, 2018 .

An adaptive deep transfer learning method for bearing fault diagnosis

Ke Zhao, Xingqiu Li, Hongkai Jiang, 2020 .

Rolling bearing fault diagnosis using variational autoencoding generative adversarial networks with deep regret analysis

Shaowei Liu, Hongkai Jiang, Xingqiu Li, 2021 .

Rolling bearing health prognosis using a modified health index based hierarchical gated recurrent unit network

Haidong Shao, Hongkai Jiang, Xingqiu Li, 2019, Mechanism and Machine Theory.

A Deep Transfer Nonnegativity-Constraint Sparse Autoencoder for Rolling Bearing Fault Diagnosis With Few Labeled Data

Ruixin Wang, Ke Zhao, Hongkai Jiang, 2019, IEEE Access.

An optimal deep sparse autoencoder with gated recurrent unit for rolling bearing fault diagnosis

Ruixin Wang, Ke Zhao, Hongkai Jiang, 2019, Measurement Science and Technology.

An integrated deep multiscale feature fusion network for aeroengine remaining useful life prediction with multisensor data

Hongkai Jiang, Xingqiu Li, Tongqing Wang, 2021, Knowl. Based Syst..

Intelligent Fault Diagnosis of Rotating Machinery Based on Deep Recurrent Neural Network

Yanan Hu, Hongkai Jiang, Xingqiu Li, 2018, 2018 International Conference on Sensing,Diagnostics, Prognostics, and Control (SDPC).

An enhanced selective ensemble deep learning method for rolling bearing fault diagnosis with beetle antennae search algorithm

Ruixin Wang, Maogui Niu, Xingqiu Li, 2020 .

An optimal variational mode decomposition for rolling bearing fault feature extraction

Dongdong Wei, Haidong Shao, Ying Lin, 2019, Measurement Science and Technology.

Intelligent fault diagnosis of rolling bearing using deep wavelet auto-encoder with extreme learning machine

Haidong Shao, Hongkai Jiang, Li Xingqiu, 2018, Knowl. Based Syst..

A reinforcement neural architecture search method for rolling bearing fault diagnosis

Ruixin Wang, Shaowei Liu, Hongkai Jiang, 2020 .

A unified framework incorporating predictive generative denoising autoencoder and deep Coral network for rolling bearing fault diagnosis with unbalanced data

Hongkai Jiang, Xingqiu Li, Jianjun Zhang, 2021, Measurement.

Attention-aware temporal-spatial graph neural network with multi-sensor information fusion for fault diagnosis

Zhe Wang, Xingqiu Li, Haidong Shao, 2023, Knowl. Based Syst..

Ensemble adaptive convolutional neural networks with parameter transfer for rotating machinery fault diagnosis

Li Xingqiu, Hongkai Jiang, Ruixin Wang, 2021, Int. J. Mach. Learn. Cybern..

A global strategy based on deep learning for time‐dependent optimal reliability design

W. Kuo, Xingqiu Li, C. Ling, 2023, Qual. Reliab. Eng. Int..

Intelligent fault diagnosis of ultrasonic motors based on graph-regularized CNN-BiLSTM

Xingqiu Li, Aibo Zhang, Peng Li, 2024, Measurement Science and Technology.