Hanwen Zhang

Orcid: 0000-0001-6712-1972

Affiliations:
  • University of Science and Technology Beijing, School of Automation and Electrical Engineering, China
  • Zhejiang University, College of Control Science and Engineering, State Key Laboratory of Industrial Control Technology, Hangzhou, China (2018 - 2021)
  • Tsinghua University, Department of Automation, TNList, Beijing, China (PhD 2018)


According to our database1, Hanwen Zhang authored at least 27 papers between 2017 and 2026.

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

Timeline

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Bibliography

2026
MAML-based temporal supervised information maximizing GAN for few-shot time series data generation.
Expert Syst. Appl., 2026

2025
Toward In-Depth Mastery of Statistical Properties: Novel Stationary Moment Analysis With Application to Continuous Industrial Anomaly Detection.
IEEE Trans. Cybern., July, 2025

Release Power of Mechanism and Data Fusion: A Hierarchical Strategy for Enhanced MIQ-Related Modeling and Fault Detection in BFIP.
IEEE CAA J. Autom. Sinica, May, 2025

TKS-BLS: Temporal Kernel Stationary Broad Learning System for Enhanced Modeling, Anomaly Detection, and Incremental Learning With Application to Ironmaking Processes.
IEEE Trans. Syst. Man Cybern. Syst., January, 2025

Spatiotemporal Generative Adversarial Network for Industrial Fault Diagnosis With Imbalanced Data.
IEEE Trans. Instrum. Meas., 2025

Quality-Related Spatio-Temporal Information Analytics-Based Multiunit Synergetic Monitoring for Plant-Wide Industrial Processes.
IEEE Trans Autom. Sci. Eng., 2025

Semi-supervised high-uncertainty deep canonical variate analysis for fault diagnosis in blast furnace ironmaking.
Knowl. Based Syst., 2025

Siamese Neural Network-based stationary feature extraction for nonstationary process monitoring.
Neurocomputing, 2025

2024
From Complexity to Clarity: M2KCSVA's Nonlinear Temporal Correlation Analysis and Stationary Estimation Pave the Way for Fault Diagnosis in Ironmaking Processes.
IEEE Trans. Ind. Informatics, April, 2024

Blast Furnace Ironmaking Process Monitoring With Time-Constrained Global and Local Nonlinear Analytic Stationary Subspace Analysis.
IEEE Trans. Ind. Informatics, March, 2024

Gaussian Mixture Model-Based Wasserstein Stationary Subspace Analysis for Process Monitoring.
IEEE Trans. Instrum. Meas., 2024

Unveiling dynamics changes: Singular spectrum analysis-based method for detecting concept drift in industrial data streams.
Knowl. Based Syst., 2024

Online spatiotemporal modeling for high spatial-dimensional DPSs under nonstationary sensor layout.
Expert Syst. Appl., 2024

Data and knowledge collaborative-driven fault identification and self-healing control action inference framework for blast furnace.
Expert Syst. Appl., 2024

Linear Encryption Techniques for Counteracting Information-based Stealthy Attacks.
Proceedings of the 17th International Conference on Control, 2024

Optimal Linear Deception Attacks on Remote State Estimation with Constrained Alarm Rates: A Low-Dimensional Case.
Proceedings of the 63rd IEEE Conference on Decision and Control, 2024

2023
Adaptive dynamic inferential analytic stationary subspace analysis: A novel method for fault detection in blast furnace ironmaking process.
Inf. Sci., 2023

2022
Nonstationary Process Monitoring for Blast Furnaces Based on Consistent Trend Feature Analysis.
IEEE Trans. Control. Syst. Technol., 2022

2021
Remaining Useful Life Prediction for Degradation Processes With Dependent and Nonstationary Increments.
IEEE Trans. Instrum. Meas., 2021

Stochastic process-based degradation modeling and RUL prediction: from Brownian motion to fractional Brownian motion.
Sci. China Inf. Sci., 2021

2020
Remaining useful life prediction for multivariable stochastic degradation systems with non-Markovian diffusion processes.
Qual. Reliab. Eng. Int., 2020

Conditional random field for monitoring multimode processes with stochastic perturbations.
J. Frankl. Inst., 2020

2019
FBM-Based Remaining Useful Life Prediction for Degradation Processes With Long-Range Dependence and Multiple Modes.
IEEE Trans. Reliab., 2019

Remaining Useful Life Prediction under Multiple Fault Patterns for Degradation Processes with Long-Range Dependence.
Proceedings of the CAA Symposium on Fault Detection, 2019

RUL Prediction: Reducing Statistical Model Uncertainty Via Bayesian Model Aggregation.
Proceedings of the CAA Symposium on Fault Detection, 2019

2018
Fault detection based on augmented kernel Mahalanobis distance for nonlinear dynamic processes.
Comput. Chem. Eng., 2018

2017
Remaining Useful Life Prediction for Degradation Processes With Long-Range Dependence.
IEEE Trans. Reliab., 2017


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