Xiaoli Zhao

Orcid: 0000-0002-9803-4158

Affiliations:
  • Nanjing University of Science and Technology, Nanjing, Jiangsu, China


According to our database1, Xiaoli Zhao authored at least 42 papers between 2016 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2025
A New Intelligent Recognition Method for Surface Electromyography in IoT Systems Using OmniXceptionDBN.
IEEE Internet Things J., July, 2025

MAACCN: An Intelligent Decoupling Diagnosis Method for Compound Faults in Electrohydrostatic Actuators.
IEEE Trans. Instrum. Meas., 2025

Diffusion-Enhanced Dual-Domain Adversarial Network: A Zero-Shot Fault Diagnosis Method for Electrohydrostatic Actuators.
IEEE Trans. Instrum. Meas., 2025

Multiple classifiers inconsistency-based deep adversarial domain generalization method for cross-condition fault diagnosis in rotating systems.
Reliab. Eng. Syst. Saf., 2025

Graph isomorphism wavelet convolutional networks for small-sample fault diagnosis of rotating machinery using multi-sensor information fusion.
Expert Syst. Appl., 2025

Remaining useful life prediction of equipment using a multiobjective optimization reinforced prognostic approach.
Comput. Ind. Eng., 2025

A novel progressive domain separation network with multi-metric ensemble quantification for open set fault diagnosis of motor bearings.
Adv. Eng. Informatics, 2025

Collaborative human-computer fault diagnosis via calibrated confidence estimation.
Adv. Eng. Informatics, 2025

2024
A Graph-Embedded Subdomain Adaptation Approach for Remaining Useful Life Prediction of Industrial IoT Systems.
IEEE Internet Things J., July, 2024

Model-Assisted Multi-source Fusion Hypergraph Convolutional Neural Networks for intelligent few-shot fault diagnosis to Electro-Hydrostatic Actuator.
Inf. Fusion, April, 2024

Unsupervised Fault Detection With Deep One-Class Classification and Manifold Distribution Alignment.
IEEE Trans. Ind. Informatics, February, 2024

Complex augmented representation network for transferable health prognosis of rolling bearing considering dynamic covariate shift.
Reliab. Eng. Syst. Saf., January, 2024

Source-free domain adaptation for transferable remaining useful life prediction of machine considering source data absence.
Reliab. Eng. Syst. Saf., 2024

Deep temporal-spectral domain adaptation for bearing fault diagnosis.
Knowl. Based Syst., 2024

Online Knowledge Distillation for Machine Health Prognosis Considering Edge Deployment.
IEEE Internet Things J., 2024

Cost-sensitive learning considering label and feature distribution consistency: A novel perspective for health prognosis of rotating machinery with imbalanced data.
Expert Syst. Appl., 2024

Graph structure few-shot prognostics for machinery remaining useful life prediction under variable operating conditions.
Adv. Eng. Informatics, 2024

Thermal Characteristic and Analysis of Electro-Hydrostatic Actuator.
IEEE Access, 2024

2023
Machinery cross domain degradation prognostics considering compound domain shifts.
Reliab. Eng. Syst. Saf., November, 2023

Remaining useful life prediction of bearings using multi-source adversarial online regression under online unknown conditions.
Expert Syst. Appl., October, 2023

Intelligent Fault Diagnosis of Gearbox Under Variable Working Conditions With Adaptive Intraclass and Interclass Convolutional Neural Network.
IEEE Trans. Neural Networks Learn. Syst., September, 2023

Fault diagnosis of bearings using a two-stage transfer alignment approach with semantic consistency and entropy loss.
Expert Syst. Appl., September, 2023

Semi-supervised machinery health assessment framework via temporal broad learning system embedding manifold regularization with unlabeled data.
Expert Syst. Appl., July, 2023

Incremental Learning for Remaining Useful Life Prediction via Temporal Cascade Broad Learning System With Newly Acquired Data.
IEEE Trans. Ind. Informatics, April, 2023

A Novel Multisensor Fusion Transformer and Its Application Into Rotating Machinery Fault Diagnosis.
IEEE Trans. Instrum. Meas., 2023

Picture-in-Picture Strategy-Based Complex Graph Neural Network for Remaining Useful Life Prediction of Rotating Machinery.
IEEE Trans. Instrum. Meas., 2023

Multiscale Deep Graph Convolutional Networks for Intelligent Fault Diagnosis of Rotor-Bearing System Under Fluctuating Working Conditions.
IEEE Trans. Ind. Informatics, 2023

Intelligent Health Assessment of Aviation Bearing Based on Deep Transfer Graph Convolutional Networks under Large Speed Fluctuations.
Sensors, 2023

Global contextual multiscale fusion networks for machine health state identification under noisy and imbalanced conditions.
Reliab. Eng. Syst. Saf., 2023

Deep imbalanced domain adaptation for transfer learning fault diagnosis of bearings under multiple working conditions.
Reliab. Eng. Syst. Saf., 2023

Domain generalization via adversarial out-domain augmentation for remaining useful life prediction of bearings under unseen conditions.
Knowl. Based Syst., 2023

2022
An adversarial transfer network with supervised metric for remaining useful life prediction of rolling bearing under multiple working conditions.
Reliab. Eng. Syst. Saf., 2022

Semi-supervised double attention guided assessment approach for remaining useful life of rotating machinery.
Reliab. Eng. Syst. Saf., 2022

Intelligent machinery health prognostics under variable operation conditions with limited and variable-length data.
Adv. Eng. Informatics, 2022

2021
Multiple-Order Graphical Deep Extreme Learning Machine for Unsupervised Fault Diagnosis of Rolling Bearing.
IEEE Trans. Instrum. Meas., 2021

Semisupervised Deep Sparse Auto-Encoder With Local and Nonlocal Information for Intelligent Fault Diagnosis of Rotating Machinery.
IEEE Trans. Instrum. Meas., 2021

Semisupervised Graph Convolution Deep Belief Network for Fault Diagnosis of Electormechanical System With Limited Labeled Data.
IEEE Trans. Ind. Informatics, 2021

Meta deep learning based rotating machinery health prognostics toward few-shot prognostics.
Appl. Soft Comput., 2021

2020
Fault Diagnosis Framework of Rolling Bearing Using Adaptive Sparse Contrative Auto-Encoder With Optimized Unsupervised Extreme Learning Machine.
IEEE Access, 2020

2019
A new Local-Global Deep Neural Network and its application in rotating machinery fault diagnosis.
Neurocomputing, 2019

2018
Fault diagnosis of rolling bearing based on feature reduction with global-local margin Fisher analysis.
Neurocomputing, 2018

2016
A method to integrate KSSOMFA and WKNN together on faults identification of rotating machinery.
Proceedings of the 13th International Conference on Ubiquitous Robots and Ambient Intelligence, 2016


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