Ping Wu
Orcid: 0000-0002-2729-9669Affiliations:
- Zhejiang Sci-Tech University, Faculty of Mechanical Engineering and Automation, School of Information Science and Engineering, Hangzhou, China
- Zhejiang University, Hangzhou, China (PhD 2009)
According to our database1,
Ping Wu
authored at least 23 papers
between 2018 and 2025.
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Bibliography
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
VMD-SE-DCNN-CBAM: An Intelligent Cavitation Recognition Method for Canned Motor Pump.
IEEE Trans. Instrum. Meas., 2025
2024
SFENOSA: A Novel KPI-Related Process Monitoring Method by Slow Feature Extraction and Elastic Net Orthonormal Subspace Analysis.
IEEE Trans. Ind. Informatics, November, 2024
Data-Driven Joint Fault Diagnosis Based on RMK-ASSA and DBSKNet for Blast Furnace Iron-Making Process.
IEEE Trans Autom. Sci. Eng., July, 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
2023
Novel Data-Driven Deep Learning Assisted CVA for Ironmaking System Prediction and Control.
IEEE Trans. Circuits Syst. II Express Briefs, December, 2023
A Local Dynamic Broad Kernel Stationary Subspace Analysis for Monitoring Blast Furnace Ironmaking Process.
IEEE Trans. Ind. Informatics, April, 2023
IEEE Trans. Instrum. Meas., 2023
Adaptive dynamic inferential analytic stationary subspace analysis: A novel method for fault detection in blast furnace ironmaking process.
Inf. Sci., 2023
Quality-related Process Monitoring based on Analytic Stationary Subspace Analysis and Kernel Projection To Latent Structures.
Proceedings of the CAA Symposium on Fault Detection, 2023
2022
Fault Diagnosis of Blast Furnace Iron-Making Process With a Novel Deep Stationary Kernel Learning Support Vector Machine Approach.
IEEE Trans. Instrum. Meas., 2022
Sensors, 2022
2021
Data-Driven Fault Diagnosis Using Deep Canonical Variate Analysis and Fisher Discriminant Analysis.
IEEE Trans. Ind. Informatics, 2021
Data-Driven Incipient Fault Detection via Canonical Variate Dissimilarity and Mixed Kernel Principal Component Analysis.
IEEE Trans. Ind. Informatics, 2021
Sensors, 2021
2020
Fault-Tolerant Individual Pitch Control of Floating Offshore Wind Turbines via Subspace Predictive Repetitive Control.
CoRR, 2020
Fast Adaptive Fault Accommodation in Floating Offshore Wind Turbines via Model-Based Fault Diagnosis and Subspace Predictive Repetitive Control.
CoRR, 2020
Fault Diagnosis of the 10MW Floating Offshore Wind Turbine Benchmark: a Mixed Model and Signal-based Approach.
CoRR, 2020
Fault Detection of the Mooring system in Floating Offshore Wind Turbines based on the Wave-excited Linear Model.
CoRR, 2020
2019
Local and Global Randomized Principal Component Analysis for Nonlinear Process Monitoring.
IEEE Access, 2019
Sparse Kernel Principal Component Analysis via Sequential Approach for Nonlinear Process Monitoring.
IEEE Access, 2019
2018
Event-Triggered H∞ Filtering for Multiagent Systems with Markovian Switching Topologies.
J. Control. Sci. Eng., 2018