Area of research
Control and Systems Engineering · Electrical and Electronic Engineering
Research interest
Research interests include Computer science, Turbine, Control theory (sociology), Fault (geology), Fault detection and isolation, and Wind power.
A data-driven integrated framework for collaborative prediction and optimisation of hot-rolled steel strip shape
A novel Causality-Constrained Synchronous Spatio-Temporal Graph Convolutional Networks for fault diagnosis in large-scale industrial processes
An Interpretable Machine Learning Ensemble Approach for Fault Detection in Floating Offshore Wind Turbines
An Integrated Distributed Fault Diagnosis Framework for Large-Scale Industrial Processes Based on Spatio–Temporal Causal Analysis
Virtual Node-Based Risk Assessment for Hidden and Cascading Failures in Production Lines
Dynamic Causal Entropy-Spatiotemporal Convolutional Network for Quality-Related Fault Diagnosis of Large-Scale Industrial Processes
Kinematic Guidance Using Virtual Reference Point for Underactuated Marine Vehicles with Sideslip Compensation
Jarque-Bera-Based Artificial Neural Correlation Analysis for Nonlinear and Non-Gaussian Process Monitoring
Fault Propagation Analysis for Manufacturing Process Monitoring via a Temporal Causal Modeling Algorithm
Joint Distribution Alignment via Mutual Information for Cross-Device Fault Diagnosis
Wind Turbine Fault Diagnosis with Artificial Intelligence Tools
Enhancing Aerospace Fault Diagnosis With Conditioned Multiscale Generative Adversarial Networks
Fault detection in nonstationary industrial processes via kolmogorov-arnold networks with test-time training
Deep Learning for Fault Diagnosis
Advancing Fault Detection in Floating Offshore Wind Turbines: An Interpretable Machine Learning Ensemble Approach
Data-Driven Fault Detection in Floating Offshore Wind Turbines Using Machine Learning and Benchmark Simulations
Feature Generating Network With Attribute-Consistency for Zero-Shot Fault Diagnosis
Performance Evaluation of Fractional Proportional–Integral–Derivative Controllers Tuned by Heuristic Algorithms for Nonlinear Interconnected Tanks
Optimal Fault-Tolerant Control for Large-Scale Interconnected Systems With State Constraints
Wind Turbine Blade Monitoring via Deep Learning and Acoustic Aerodynamic Signals
Artificial Neural Network-based Wake Steering Control under the Time-varying Inflow<sup>*</sup>
Wind Turbine Data-Driven Intelligent Fault Detection
Model-Free Adaptive Fault-Tolerant Control for Offshore Wind Turbines
Artificial Intelligence Tools for Wind Turbine Blade Monitoring
RETRACTED: Data–Driven Adaptive Fault–Tolerant Control for Floating Offshore Wind Turbines
An Intelligent Strategy for Wind Turbine Condition Monitoring
RETRACTED: Data–Driven Adaptive Fault–Tolerant Control for Floating Offshore Wind Turbines
Meta-Learning With Distributional Similarity Preference for Few-Shot Fault Diagnosis Under Varying Working Conditions
Dynamic Neural Network Architecture Design for Predicting Remaining Useful Life of Dynamic Processes
Improved Generative Adversarial Networks With Filtering Mechanism for Fault Data Augmentation