李翔｜江苏大学｜学者主页

2026

DCIA-SOH: Degradation-causal invariant adaptation for cross-dataset battery state-of-health prediction via uncertainty-guided pseudo-labeling

Wei Zhang, Tian-Li Xue, Xiang Li

Neurocomputing

DOI

2024

Domain Generalization Prognosis Method for Lithium-ion Battery State of Health with Transformer and Multi-kernel MMD

Ya-Fei Zhu, Tianyi Guo, Xiang Li, Yewei Zhang, Wei Zhang

Journal of Dynamics Monitoring and Diagnostics

DOI

2023

Cross-Domain Prognostic Method of Lithium-Ion Battery in New Energy Electric Aircraft With Domain Adaptation

Ya-Fei Zhu, Xiang Li, Yewei Zhang, Wei Zhang

IEEE Sensors Journal

DOI

2022

Data Amplification for Bearing Remaining Useful Life Prediction Based on Generative Adversarial Network

Luyao Lei, Xiang Li, Juan Wen, Junhao Miao

Wireless Communications and Mobile Computing

DOI

2022

Deep Residual Net-Based Prognosis Method for Lithium-ion Batteries with Information Fusion from Different Scales

Ya-Fei Zhu, Xiang Li, Wei Zhang

2022 Global Reliability and Prognostics and Health Management (PHM-Yantai)

DOI

2021

Federated learning for machinery fault diagnosis with dynamic validation and self-supervision

Wei Zhang, Xiang Li, Hui Ma, Zhong Luo, Xu Li

Knowledge-Based Systems

DOI

2021

A multi-stage semi-supervised learning approach for intelligent fault diagnosis of rolling bearing using data augmentation and metric learning

Kun Yu, T. Lin, Hui Ma, Xiang Li, Xu Li

DOI

2021

Interpretability of deep convolutional neural networks on rolling bearing fault diagnosis

Huixin Yang, Xiang Li, Wei Zhang

Measurement science and technology

DOI

2021

Intelligent fault diagnosis methodology under varying operating conditions using multi-layer domain adversarial learning strategy

Nan-Xi Xu, Xiang Li

International Journal of Dynamics and Control

DOI

2021

Open-Set Domain Adaptation in Machinery Fault Diagnostics Using Instance-Level Weighted Adversarial Learning

Wei Zhang, Xiang Li, Hui Ma, Zhong Luo, Xu Li

IEEE Transactions on Industrial Informatics

DOI

2021

Deep Learning-Based Partial Domain Adaptation Method on Intelligent Machinery Fault Diagnostics

Xiang Li, Wei Zhang

IEEE transactions on industrial electronics (1982. Print)

DOI

2021

Data privacy preserving federated transfer learning in machinery fault diagnostics using prior distributions

Wei Zhang, Xiang Li

Structural Health Monitoring

DOI

2021

Degradation Alignment in Remaining Useful Life Prediction Using Deep Cycle-Consistent Learning

Xiang Li, Wei Zhang, Hui Ma, Zhong Luo, Xu Li

IEEE Transactions on Neural Networks and Learning Systems

DOI

2021

Universal Domain Adaptation in Fault Diagnostics With Hybrid Weighted Deep Adversarial Learning

Wei Zhang, Xiang Li, Hui Ma, Zhong Luo, Xu Li

IEEE Transactions on Industrial Informatics

DOI

2021

Federated Transfer Learning for Intelligent Fault Diagnostics Using Deep Adversarial Networks With Data Privacy

Wei Zhang, Xiang Li

IEEE/ASME transactions on mechatronics

DOI

2020

Domain generalization in rotating machinery fault diagnostics using deep neural networks

Xiang Li, Wei Zhang, Hui Ma, Zhong Luo, Xu Li

Neurocomputing

DOI

2020

Deep learning-based prognostic approach for lithium-ion batteries with adaptive time-series prediction and on-line validation

Wei Zhang, Xiang Li, Xu Li

DOI

2020

Partial transfer learning in machinery cross-domain fault diagnostics using class-weighted adversarial networks

Xiang Li, Wei Zhang, Hui Ma, Zhong Luo, Xu Li

Neural Networks

DOI

2020

A consistency regularization based semi-supervised learning approach for intelligent fault diagnosis of rolling bearing

Kun Yu, Hui Ma, T. Lin, Xiang Li

DOI

2020

Intelligent cross-machine fault diagnosis approach with deep auto-encoder and domain adaptation

Xiang Li, Xiaodong Jia, Wei Zhang, Hui Ma, Zhong Luo, Xu Li

Neurocomputing

DOI

2020

Simulation data driven weakly supervised adversarial domain adaptation approach for intelligent cross-machine fault diagnosis

Kun Yu, Qiang Fu, Hui Ma, Tian-Ran Lin, Xiang Li

Structural Health Monitoring

DOI

2020

Machinery fault diagnosis with imbalanced data using deep generative adversarial networks

Wei Zhang, Xiang Li, Xiaoyu Jia, Hui Ma, Zhong Luo, Xu Li

DOI

2020

Deep representation clustering-based fault diagnosis method with unsupervised data applied to rotating machinery

Xiang Li, Xu Li, Hui Ma

DOI

2020

Diagnosing Rotating Machines With Weakly Supervised Data Using Deep Transfer Learning

Xiang Li, Wei Zhang, Q. Ding, Xu Li

IEEE Transactions on Industrial Informatics

DOI

2020

Deep Learning-Based Machinery Fault Diagnostics With Domain Adaptation Across Sensors at Different Places

Xiang Li, Wei Zhang, Nan-Xi Xu, Q. Ding

IEEE transactions on industrial electronics (1982. Print)

DOI

2020

Data alignments in machinery remaining useful life prediction using deep adversarial neural networks

Xiang Li, Wei Zhang, Hui Ma, Zhong Luo, Xu Li

Knowledge-Based Systems

DOI

2019

Understanding and improving deep learning-based rolling bearing fault diagnosis with attention mechanism

Xiang Li, Wei Zhang, Q. Ding

Signal Processing

DOI

2019

Cross-Domain Fault Diagnosis of Rolling Element Bearings Using Deep Generative Neural Networks

Xiang Li, Wei Zhang, Q. Ding

IEEE transactions on industrial electronics (1982. Print)

DOI

2019

Multi-Layer domain adaptation method for rolling bearing fault diagnosis

Xiang Li, Wei Zhang, Q. Ding, Jian-Qiao Sun

Signal Processing

DOI

2019

Cross-Domain Machinery Fault Diagnosis Using Adversarial Network with Conditional Alignments

Nan-Xi Xu, Xiang Li

Prognostics and System Health Management Conference

DOI

2019

Deep residual learning-based fault diagnosis method for rotating machinery.

Wei Zhang, Xiang Li, Q. Ding

ISA transactions

DOI

2018

A robust intelligent fault diagnosis method for rolling element bearings based on deep distance metric learning

Xiang Li, Wei Zhang, Q. Ding

Neurocomputing

DOI

2018

Intelligent rotating machinery fault diagnosis based on deep learning using data augmentation

Xiang Li, Wei Zhang, Q. Ding, Jian-Qiao Sun

Journal of Intelligent Manufacturing

DOI

李翔

精选作品

期刊论文

DCIA-SOH: Degradation-causal invariant adaptation for cross-dataset battery state-of-health prediction via uncertainty-guided pseudo-labeling

Domain Generalization Prognosis Method for Lithium-ion Battery State of Health with Transformer and Multi-kernel MMD

Cross-Domain Prognostic Method of Lithium-Ion Battery in New Energy Electric Aircraft With Domain Adaptation

Data Amplification for Bearing Remaining Useful Life Prediction Based on Generative Adversarial Network

Deep Residual Net-Based Prognosis Method for Lithium-ion Batteries with Information Fusion from Different Scales

Federated learning for machinery fault diagnosis with dynamic validation and self-supervision

A multi-stage semi-supervised learning approach for intelligent fault diagnosis of rolling bearing using data augmentation and metric learning

Interpretability of deep convolutional neural networks on rolling bearing fault diagnosis

Intelligent fault diagnosis methodology under varying operating conditions using multi-layer domain adversarial learning strategy

Open-Set Domain Adaptation in Machinery Fault Diagnostics Using Instance-Level Weighted Adversarial Learning

Deep Learning-Based Partial Domain Adaptation Method on Intelligent Machinery Fault Diagnostics

Data privacy preserving federated transfer learning in machinery fault diagnostics using prior distributions

Degradation Alignment in Remaining Useful Life Prediction Using Deep Cycle-Consistent Learning

Universal Domain Adaptation in Fault Diagnostics With Hybrid Weighted Deep Adversarial Learning

Federated Transfer Learning for Intelligent Fault Diagnostics Using Deep Adversarial Networks With Data Privacy

Domain generalization in rotating machinery fault diagnostics using deep neural networks

Deep learning-based prognostic approach for lithium-ion batteries with adaptive time-series prediction and on-line validation

Partial transfer learning in machinery cross-domain fault diagnostics using class-weighted adversarial networks

A consistency regularization based semi-supervised learning approach for intelligent fault diagnosis of rolling bearing

Intelligent cross-machine fault diagnosis approach with deep auto-encoder and domain adaptation

Simulation data driven weakly supervised adversarial domain adaptation approach for intelligent cross-machine fault diagnosis

Machinery fault diagnosis with imbalanced data using deep generative adversarial networks

Deep representation clustering-based fault diagnosis method with unsupervised data applied to rotating machinery

Diagnosing Rotating Machines With Weakly Supervised Data Using Deep Transfer Learning

Deep Learning-Based Machinery Fault Diagnostics With Domain Adaptation Across Sensors at Different Places

Data alignments in machinery remaining useful life prediction using deep adversarial neural networks

Understanding and improving deep learning-based rolling bearing fault diagnosis with attention mechanism

Cross-Domain Fault Diagnosis of Rolling Element Bearings Using Deep Generative Neural Networks

Multi-Layer domain adaptation method for rolling bearing fault diagnosis

Cross-Domain Machinery Fault Diagnosis Using Adversarial Network with Conditional Alignments

Deep residual learning-based fault diagnosis method for rotating machinery.

A robust intelligent fault diagnosis method for rolling element bearings based on deep distance metric learning

Intelligent rotating machinery fault diagnosis based on deep learning using data augmentation