Khang huynh

Lecturer

University of Agder

Norway

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Dr. Khang Huynh is a Lecturer at the University of Agder, Norway. His research primarily focuses on artificial intelligence applications in power generation, fault diagnosis in electrical systems, and predictive maintenance for renewable energy technologies. Recent publications highlight advancements in AI-based prediction models, digital twin technology, and the integration of multiple renewable energy sources.

Khang huynh

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Articles (17)

The Impact of the Weather Forecast Model on Improving AI-Based Power Generation Predictions through BiLSTM Networks

A Few-Shot Open-Circuit Fault Diagnosis of F-Type Inverters Using CGAN-Based Vision Transformer

Time–Frequency Analysis and Fault Prediction of Motor Bearings Using Millimeter-Wave Radar

Digital Twin as a Virtual Sensor for Wind Turbine Applications

Exploring the Limits of Early Predictive Maintenance in Wind Turbines Applying an Anomaly Detection Technique

A Current Spectrum-Based Algorithm for Fault Detection of Electrical Machines Using Low-Power Data Acquisition Devices

Robust Multiple-Fault Diagnosis of PMSM Drives Under Variant Operations and Noisy Conditions

Robust Active Learning Multiple Fault Diagnosis of PMSM Drives with Sensorless Control under Dynamic Operations and Imbalanced Datasets

Integrated Multiport DC-DC and Multilevel Converters for Multiple Renewable Energy Source Integration

Novel Isolated Multiport DC Converter with Natural Bipolar Symmetry for Renewable Energy Source Integration to DC Grids

Power Line Monitoring through Data Integrity Analysis with Q-Learning Based Data Analysis Network

Signal Spectrum-Based Machine Learning Approach for Fault Prediction and Maintenance of Electrical Machines

Real-Time Detection of Incipient Inter-Turn Short Circuit and Sensor Faults in Permanent Magnet Synchronous Motor Drives Based on Generalized Likelihood Ratio Test and Structural Analysis

Cascaded Multilevel Inverter-Based Asymmetric Static Synchronous Compensator of Reactive Power

Mixed Fault Classification of Sensorless PMSM Drive in Dynamic Operations Based on External Stray Flux Sensors

Methods of Condition Monitoring and Fault Detection for Electrical Machines

Field Reconstruction for Modelling Multiple Faults in Permanent Magnet Synchronous Motors in Transient States

Collaborators (7)

Karolina Kudelina

Toomas Vaimann

Ants Kallaste

Jagath Sri Lal Senanayaka

LINGA REDDY CENKERAMADDI

Ajit Jha

Anton Rassõlkin

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