Hongkai Jiang

Orcid: 0000-0001-6180-4641

According to our database1, Hongkai Jiang authored at least 45 papers between 2017 and 2025.

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

Timeline

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Bibliography

2025
A novel reinforcement learning agent for rotating machinery fault diagnosis with data augmentation.
Reliab. Eng. Syst. Saf., 2025

2024
Rolling bearing intelligent fault diagnosis towards variable speed and imbalanced samples using multiscale dynamic supervised contrast learning.
Reliab. Eng. Syst. Saf., March, 2024

An interpretable multiscale lifting wavelet contrast network for planetary gearbox fault diagnosis with small samples.
Reliab. Eng. Syst. Saf., 2024

Deep discriminative sparse representation learning for machinery fault diagnosis.
Eng. Appl. Artif. Intell., 2024

Global wavelet-integrated residual frequency attention regularized network for hypersonic flight vehicle fault diagnosis with imbalanced data.
Eng. Appl. Artif. Intell., 2024

Dynamic normalization supervised contrastive network with multiscale compound attention mechanism for gearbox imbalanced fault diagnosis.
Eng. Appl. Artif. Intell., 2024

A task-oriented theil index-based meta-learning network with gradient calibration strategy for rotating machinery fault diagnosis with limited samples.
Adv. Eng. Informatics, 2024

Multi-sensor data fusion-enabled lightweight convolutional double regularization contrast transformer for aerospace bearing small samples fault diagnosis.
Adv. Eng. Informatics, 2024

2023
A dynamic spectrum loss generative adversarial network for intelligent fault diagnosis with imbalanced data.
Eng. Appl. Artif. Intell., November, 2023

Digital twin-assisted multiscale residual-self-attention feature fusion network for hypersonic flight vehicle fault diagnosis.
Reliab. Eng. Syst. Saf., July, 2023

Conditional distribution-guided adversarial transfer learning network with multi-source domains for rolling bearing fault diagnosis.
Adv. Eng. Informatics, April, 2023

Adaptive variational autoencoding generative adversarial networks for rolling bearing fault diagnosis.
Adv. Eng. Informatics, April, 2023

Intelligent fault diagnosis of rotating machinery using a multi-source domain adaptation network with adversarial discrepancy matching.
Reliab. Eng. Syst. Saf., 2023

Intelligent fault diagnosis of rolling bearing based on a deep transfer learning network.
Proceedings of the IEEE International Conference on Prognostics and Health Management, 2023

Fault diagnosis of rolling bearing using a transfer ensemble deep reinforcement learning method.
Proceedings of the IEEE International Conference on Prognostics and Health Management, 2023

2022
Modified Deep Autoencoder Driven by Multisource Parameters for Fault Transfer Prognosis of Aeroengine.
IEEE Trans. Ind. Electron., 2022

RTSfM: Real-Time Structure From Motion for Mosaicing and DSM Mapping of Sequential Aerial Images With Low Overlap.
IEEE Trans. Geosci. Remote. Sens., 2022

A new data generation approach with modified Wasserstein auto-encoder for rotating machinery fault diagnosis with limited fault data.
Knowl. Based Syst., 2022

Data-augmented wavelet capsule generative adversarial network for rolling bearing fault diagnosis.
Knowl. Based Syst., 2022

An integrated deep multiscale feature fusion network for aeroengine remaining useful life prediction with multisensor data.
Knowl. Based Syst., 2022

A novel transfer learning fault diagnosis method based on Manifold Embedded Distribution Alignment with a little labeled data.
J. Intell. Manuf., 2022

A Gaussian-guided adversarial adaptation transfer network for rolling bearing fault diagnosis.
Adv. Eng. Informatics, 2022

A deep feature enhanced reinforcement learning method for rolling bearing fault diagnosis.
Adv. Eng. Informatics, 2022

A deep feature alignment adaptation network for rolling bearing intelligent fault diagnosis.
Adv. Eng. Informatics, 2022

Machine fault diagnosis with small sample based on variational information constrained generative adversarial network.
Adv. Eng. Informatics, 2022

A reinforcement ensemble deep transfer learning network for rolling bearing fault diagnosis with Multi-source domains.
Adv. Eng. Informatics, 2022

A Deep Ensemble Learning Model for Rolling Bearing Fault Diagnosis.
Proceedings of the 2022 IEEE International Conference on Prognostics and Health Management, 2022

Imbalanced fault diagnosis of rolling bearing using a deep gradient improved generative adversarial network.
Proceedings of the 2022 IEEE International Conference on Prognostics and Health Management, 2022

2021
Fast Georeferenced Aerial Image Stitching With Absolute Rotation Averaging and Planar- Restricted Pose Graph.
IEEE Trans. Geosci. Remote. Sens., 2021

HighStitch: High Altitude Georeferenced Aerial Images Stitching for Rocking Telephoto Lens.
IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., 2021

Ensemble adaptive convolutional neural networks with parameter transfer for rotating machinery fault diagnosis.
Int. J. Mach. Learn. Cybern., 2021

Joint distribution adaptation network with adversarial learning for rolling bearing fault diagnosis.
Knowl. Based Syst., 2021

Rolling bearing fault diagnosis using optimal ensemble deep transfer network.
Knowl. Based Syst., 2021

Svar: A Tiny C++ Header Brings Unified Interface for Multiple programming Languages.
CoRR, 2021

2020
Real-Time Orthophoto Mosaicing on Mobile Devices for Sequential Aerial Images with Low Overlap.
Remote. Sens., 2020

A deep transfer maximum classifier discrepancy method for rolling bearing fault diagnosis under few labeled data.
Knowl. Based Syst., 2020

Enhanced deep gated recurrent unit and complex wavelet packet energy moment entropy for early fault prognosis of bearing.
Knowl. Based Syst., 2020

2019
A Deep Transfer Nonnegativity-Constraint Sparse Autoencoder for Rolling Bearing Fault Diagnosis With Few Labeled Data.
IEEE Access, 2019

GSLAM: A General SLAM Framework and Benchmark.
Proceedings of the 2019 IEEE/CVF International Conference on Computer Vision, 2019

2018
Electric Locomotive Bearing Fault Diagnosis Using a Novel Convolutional Deep Belief Network.
IEEE Trans. Ind. Electron., 2018

Intelligent fault diagnosis of rolling bearing using deep wavelet auto-encoder with extreme learning machine.
Knowl. Based Syst., 2018

A feature fusion deep belief network method for intelligent fault diagnosis of rotating machinery.
J. Intell. Fuzzy Syst., 2018

Rolling bearing fault detection using continuous deep belief network with locally linear embedding.
Comput. Ind., 2018

Unsupervised Feature Learning of Gearbox Fault Using Stacked Wavelet Auto-encoder.
Proceedings of the 2018 IEEE International Conference on Prognostics and Health Management, 2018

2017
An enhancement deep feature fusion method for rotating machinery fault diagnosis.
Knowl. Based Syst., 2017


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