Jun Wu

Orcid: 0000-0002-8657-5475

Affiliations:
  • Huazhong University of Science and Technology, School of Naval Architecture and Ocean Engineering, Wuhan, China
  • Huazhong University of Science and Technology, Department of Mechanical Engineering, Wuhan, China (PhD 2008)


According to our database1, Jun Wu authored at least 37 papers between 2008 and 2024.

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Bibliography

2024
Deep Learning-Based Bearing Fault Diagnosis Using a Trusted Multiscale Quadratic Attention-Embedded Convolutional Neural Network.
IEEE Trans. Instrum. Meas., 2024

2023
Deep Bidirectional Recurrent Neural Networks Ensemble for Remaining Useful Life Prediction of Aircraft Engine.
IEEE Trans. Cybern., April, 2023

Hybrid scheme through read-first-LSTM encoder-decoder and broad learning system for bearings degradation monitoring and remaining useful life estimation.
Adv. Eng. Informatics, April, 2023

Deep Attention Relation Network: A Zero-Shot Learning Method for Bearing Fault Diagnosis Under Unknown Domains.
IEEE Trans. Reliab., March, 2023

Deep convolutional transfer learning-based structural damage detection with domain adaptation.
Appl. Intell., March, 2023

Relational Conduction Graph Network for Intelligent Fault Diagnosis of Rotating Machines Under Small Fault Samples.
IEEE Trans. Instrum. Meas., 2023

Residual shrinkage transformer relation network for intelligent fault detection of industrial robot with zero-fault samples.
Knowl. Based Syst., 2023

Deep transfer learning-based damage detection of composite structures by fusing monitoring data with physical mechanism.
Eng. Appl. Artif. Intell., 2023

2022
Wide Residual Relation Network-Based Intelligent Fault Diagnosis of Rotating Machines with Small Samples.
Sensors, 2022

Dimensionality reduce-based for remaining useful life prediction of machining tools with multisensor fusion.
Reliab. Eng. Syst. Saf., 2022

Health indicator construction for degradation assessment by embedded LSTM-CNN​ autoencoder and growing self-organized map.
Knowl. Based Syst., 2022

Multi-dimensional recurrent neural network for remaining useful life prediction under variable operating conditions and multiple fault modes.
Appl. Soft Comput., 2022

A deep learning-based two-stage prognostic approach for remaining useful life of rolling bearing.
Appl. Intell., 2022

Multi-mode signals driven damage detection for composite structures by ensemble generalized multiclass support vector machine.
Proceedings of the 2022 IEEE International Conference on Prognostics and Health Management, 2022

2021
Convolutional Neural Network-Based Bayesian Gaussian Mixture for Intelligent Fault Diagnosis of Rotating Machinery.
IEEE Trans. Instrum. Meas., 2021

Remaining Useful Life Prognosis Based on Ensemble Long Short-Term Memory Neural Network.
IEEE Trans. Instrum. Meas., 2021

Intelligent fault diagnosis of rotating machinery based on continuous wavelet transform-local binary convolutional neural network.
Knowl. Based Syst., 2021

Sensor data-driven structural damage detection based on deep convolutional neural networks and continuous wavelet transform.
Appl. Intell., 2021

A convolutional neural network based degradation indicator construction and health prognosis using bidirectional long short-term memory network for rolling bearings.
Adv. Eng. Informatics, 2021

2020
Intelligent Fault Diagnosis via Semisupervised Generative Adversarial Nets and Wavelet Transform.
IEEE Trans. Instrum. Meas., 2020

Ensemble extreme learning machines for compound-fault diagnosis of rotating machinery.
Knowl. Based Syst., 2020

Single and simultaneous fault diagnosis of gearbox via a semi-supervised and high-accuracy adversarial learning framework.
Knowl. Based Syst., 2020

Stacked pruning sparse denoising autoencoder based intelligent fault diagnosis of rolling bearings.
Appl. Soft Comput., 2020

2019
Machine Health Monitoring Using Adaptive Kernel Spectral Clustering and Deep Long Short-Term Memory Recurrent Neural Networks.
IEEE Trans. Ind. Informatics, 2019

Degradation Data-Driven Time-To-Failure Prognostics Approach for Rolling Element Bearings in Electrical Machines.
IEEE Trans. Ind. Electron., 2019

Sensor Data-Driven Bearing Fault Diagnosis Based on Deep Convolutional Neural Networks and S-Transform.
Sensors, 2019

Compound Fault Diagnosis of Gearboxes via Multi-label Convolutional Neural Network and Wavelet Transform.
Comput. Ind., 2019

Health Degradation Monitoring of Rolling Element Bearing by Growing Self- Organizing Mapping and Clustered Support Vector Machine.
IEEE Access, 2019

Multisensory Data-Driven Health Degradation Monitoring of Machining Tools by Generalized Multiclass Support Vector Machine.
IEEE Access, 2019

Intelligent Fault Diagnosis of Rolling Element Bearing Based on Convolutional Neural Network and Frequency Spectrograms.
Proceedings of the 2019 IEEE International Conference on Prognostics and Health Management, 2019

2018
Selective maintenance scheduling under stochastic maintenance quality with multiple maintenance actions.
Int. J. Prod. Res., 2018

Multi-sensor information fusion for remaining useful life prediction of machining tools by adaptive network based fuzzy inference system.
Appl. Soft Comput., 2018

An Economical Optimization Model of Non-Periodic Maintenance Decision for Deteriorating System.
IEEE Access, 2018

Study on Health Assessment and Residual Useful Life Prediction of Wind Turbine.
Proceedings of the 2018 IEEE/ASME International Conference on Advanced Intelligent Mechatronics, 2018

2017
Design a degradation condition monitoring system scheme for rolling bearing using EMD and PCA.
Ind. Manag. Data Syst., 2017

2015
Failure time prediction for mechanical device based on the degradation sequence.
J. Intell. Manuf., 2015

2008
Reliability Assessment of Machining Accuracy on Support Vector Machine.
Proceedings of the Intelligent Robotics and Applications, First International Conference, 2008


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