Jie Dong

Orcid: 0000-0001-7585-6637

Affiliations:
  • University of Science and Technology Beijing, School of Automation and Electrical Engineering, China (PhD 2007)


According to our database1, Jie Dong authored at least 55 papers between 2010 and 2024.

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

Timeline

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Bibliography

2024
A novel method of neural network model predictive control integrated process monitoring and applications to hot rolling process.
Expert Syst. Appl., March, 2024

A Two-Layer Distributed Fault Diagnosis Method Based on Correlation Feature Transfer for Large-Scale Sequential Process Industries.
IEEE Trans. Instrum. Meas., 2024

2023
A Novel Distributed CVRAE-Based Spatio-Temporal Process Monitoring Method With Its Application.
IEEE Trans. Ind. Informatics, November, 2023

A Robust Fault Classification Method for Streaming Industrial Data Based on Wasserstein Generative Adversarial Network and Semi-Supervised Ladder Network.
IEEE Trans. Instrum. Meas., 2023

Distributed Quality-Related Process Monitoring Framework Using Parallel DVIB-VAE-mRMR for Large-Scale Processes.
IEEE Trans. Instrum. Meas., 2023

Hierarchical Causal Graph-Based Fault Root Cause Diagnosis and Propagation Path Identification for Complex Industrial Process Monitoring.
IEEE Trans. Instrum. Meas., 2023

A comprehensive operating performance assessment framework based on distributed Siamese gated recurrent unit for hot strip mill process.
Appl. Soft Comput., 2023

Exergy-related Operating Performance Assessment for Hot Rolling Process Based on Multiple imputation and Multi-class Support Vector Data Description.
Proceedings of the 6th IEEE International Conference on Industrial Cyber-Physical Systems, 2023

2022
A Practical Root Cause Diagnosis Framework for Quality-Related Faults in Manufacturing Processes With Irregular Sampling Measurements.
IEEE Trans. Instrum. Meas., 2022

A Novel Fault Detection Method Based on the Extraction of Slow Features for Dynamic Nonstationary Processes.
IEEE Trans. Instrum. Meas., 2022

A Novel Quality-Related Incipient Fault Detection Method Based on Canonical Variate Analysis and Kullback-Leibler Divergence for Large-Scale Industrial Processes.
IEEE Trans. Instrum. Meas., 2022

A Novel Multilabel Classification Framework for Coupling Faults in Hot Rolling Processes.
IEEE Trans. Control. Syst. Technol., 2022

A new key performance indicator oriented industrial process monitoring and operating performance assessment method based on improved Hessian locally linear embedding.
Int. J. Syst. Sci., 2022

A novel distributed detection framework for quality-related faults in industrial plant-wide processes.
Neurocomputing, 2022

KPI-related operating performance assessment based on distributed ImRMR-KOCTA for hot strip mill process.
Expert Syst. Appl., 2022

Distributed Operating Performance Assessment for Hot Strip Mill Process Based on Probabilistic Support Tensor Data Description with Feature Tensor.
Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics, 2022

2021
A novel decentralized detection framework for quality-related faults in manufacturing industrial processes.
Neurocomputing, 2021

Remaining Useful Life Prediction for a Roller in a Hot Strip Mill Based on Deep Recurrent Neural Networks.
IEEE CAA J. Autom. Sinica, 2021

An extensible quality-related fault isolation framework based on dual broad partial least squares with application to the hot rolling process.
Expert Syst. Appl., 2021

Quality Anomaly Monitoring and Comprehensive Diagnosis Framework for Plant-wide Process Industries with Spatio-Temporal Coordination.
Proceedings of the CAA Symposium on Fault Detection, 2021

A Quality-related Fault Detection Method for Nonlinear Industrial Processes Based on Mixed Kernel Partial Least Squares.
Proceedings of the CAA Symposium on Fault Detection, 2021

2020
Remaining Useful Life Prediction of Lithium-Ion Batteries Based on Conditional Variational Autoencoders-Particle Filter.
IEEE Trans. Instrum. Meas., 2020

A Novel Robust Semisupervised Classification Framework for Quality-Related Coupling Faults in Manufacturing Industries.
IEEE Trans. Ind. Informatics, 2020

A Novel Hierarchical Detection and Isolation Framework for Quality-Related Multiple Faults in Large-Scale Processes.
IEEE Trans. Ind. Electron., 2020

Fault monitoring and remaining useful life prediction framework for multiple fault modes in prognostics.
Reliab. Eng. Syst. Saf., 2020

Composite adaptive control for bilateral teleoperation systems without persistency of excitation.
J. Frankl. Inst., 2020

A novel industrial process monitoring method based on improved local tangent space alignment algorithm.
Neurocomputing, 2020

Data-Driven Nonzero-Sum Game for Discrete-Time Systems Using Off-Policy Reinforcement Learning.
IEEE Access, 2020

Monitoring of Nonlinear Processes With Multiple Operating Modes Through a Novel Gaussian Mixture Variational Autoencoder Model.
IEEE Access, 2020

Just-in-Time Learning-Based Soft Sensor for Mechanical Properties of Strip Steel via Multi-Block Weighted Semisupervised Models.
IEEE Access, 2020

2019
Hierarchical Monitoring and Root-Cause Diagnosis Framework for Key Performance Indicator-Related Multiple Faults in Process Industries.
IEEE Trans. Ind. Informatics, 2019

A novel plant-wide process monitoring framework based on distributed Gap-SVDD with adaptive radius.
Neurocomputing, 2019

A deep belief network based health indicator construction and remaining useful life prediction using improved particle filter.
Neurocomputing, 2019

A New Hierarchical Framework for Detection and Isolation of Multiple Faults in Complex Industrial Processes.
IEEE Access, 2019

Composite Adaptive Control of Teleoperators With Joint Flexibility, Uncertain Parameters, and Time-Delays.
IEEE Access, 2019

An Output Probabilistic Constrained Optimal Control Algorithm Based on Multivariable MAC and its Application in Looper Control System.
IEEE Access, 2019

Quality Monitoring and Root Cause Diagnosis for Industrial Processes Based on Lasso-SAE-CCA.
IEEE Access, 2019

2018
A Common and Individual Feature Extraction-Based Multimode Process Monitoring Method With Application to the Finishing Mill Process.
IEEE Trans. Ind. Informatics, 2018

A practical propagation path identification scheme for quality-related faults based on nonlinear dynamic latent variable model and partitioned Bayesian network.
J. Frankl. Inst., 2018

Implementing multivariate statistics-based process monitoring: A comparison of basic data modeling approaches.
Neurocomputing, 2018

Root cause diagnosis of quality-related faults in industrial multimode processes using robust Gaussian mixture model and transfer entropy.
Neurocomputing, 2018

Data-Driven Quality Monitoring Techniques for Distributed Parameter Systems With Application to Hot-Rolled Strip Laminar Cooling Process.
IEEE Access, 2018

2017
An Efficient Quality-Related Fault Diagnosis Method for Real-Time Multimode Industrial Process.
J. Control. Sci. Eng., 2017

A novel dynamic non-Gaussian approach for quality-related fault diagnosis with application to the hot strip mill process.
J. Frankl. Inst., 2017

Event-triggered fault detection framework based on subspace identification method for the networked control systems.
Neurocomputing, 2017

Joint Data-Driven Fault Diagnosis Integrating Causality Graph With Statistical Process Monitoring for Complex Industrial Processes.
IEEE Access, 2017

2016
A Quality-Based Nonlinear Fault Diagnosis Framework Focusing on Industrial Multimode Batch Processes.
IEEE Trans. Ind. Electron., 2016

Quality-related process monitoring for dynamic non-Gaussian batch process with multi-phase using a new data-driven method.
Neurocomputing, 2016

2015
Quality-relevant fault detection and diagnosis for hot strip mill process with multi-specification and multi-batch measurements.
J. Frankl. Inst., 2015

Quality-related prediction and monitoring of multi-mode processes using multiple PLS with application to an industrial hot strip mill.
Neurocomputing, 2015

Adaptive total PLS based quality-relevant process monitoring with application to the Tennessee Eastman process.
Neurocomputing, 2015

2014
A new data-driven process monitoring scheme for key performance indictors with application to hot strip mill process.
J. Frankl. Inst., 2014

2012
Artificial Neural Network Based Control Strategy Research and Simulation on Robot Uncalibrated Visual Servoing System.
Proceedings of the Intelligent Science and Intelligent Data Engineering, 2012

2010
Robust coordinated control of hot strip mill multivariable system.
Proceedings of the 11th International Conference on Control, 2010

IVFH<sup>*</sup>: Real-time dynamic obstacle avoidance for mobile robots.
Proceedings of the 11th International Conference on Control, 2010


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