Wenxian Yang

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Senior Lecturer in Offshore Renewable Energy

Newcastle University

United Kingdom

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About

Wenxian Yang is a Senior Lecturer in Offshore Renewable Energy at Newcastle University, UK. His research focuses on offshore wind turbine foundations, including monitoring scour pits and enhancing motion control of floating turbines. Additionally, he investigates lithium-ion battery performance, including state-of-health estimation and fault diagnosis using advanced machine learning techniques.

Recent Grants

Grant: Close

Biomimetic Device for Stabilizing Offshore Floating Wind Turbines

Open Date: 2019-06-01

Close Date: 2020-06-01

Grant: Close

ISCF Wave 1: North East Centre for Energy Materials

Open Date: 2017-10-01

Close Date: 2021-03-01

Grant: Close

Research on an efficient and reliable bio-mimetic blade dedicated for tidal turbines

Open Date: 2015-05-01

Close Date: 2016-05-01

Grant: Close

Research on innovative signal processing techniques dedicated to wind turbine condition monitoring

Open Date: 2014-10-01

Close Date: 2015-10-01

Grant: Close

Condition monitoring techniques dedicated for wind turbine drive-train and DC-link capacitor

Open Date: 2014-03-01

Close Date: 2017-03-01

Articles (20)

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Lloyds Professor of Offshore Engineering

Newcastle University

UNITED KINGDOM

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Wenxian Yang

Research Interests

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Contact this professor

About

Recent Grants

Articles (20)

Monitoring Scour Pits around Offshore Wind Turbine Foundations for Enhanced Maintenance

Adhesive contact problem between thermoelectric material and rigid solid with slightly wavy surface

Further study of heave plate designs for enhancing motion control of floating offshore wind turbines

Mechanical fault diagnosis method based on binary neural network with adaptive depth-to-width ratio

A Meta-Learning Method for Few-Shot Multidomain State-of-Health Estimation of Lithium-Ion Batteries

Fault diagnosis method based on multimodal-deep tensor projection network under variable working conditions

Research on the output characteristics and SOC estimation method of lithium-ion batteries over a wide range of operating temperature conditions

Development and prediction of scour around offshore wind turbine monopile foundations in ebb and flow tides

Adaptable capacity estimation of lithium-ion battery based on short-duration random constant-current charging voltages and convolutional neural networks

A label-free battery state of health estimation method based on adversarial multi-domain adaptation network and relaxation voltage

Study for predicting the earthquake-induced liquefaction around the monopile foundation of offshore wind turbines

Effects of tidal turbine number on the performance of a 10 MW-class semi-submersible integrated floating wind-current system

Smart Monitoring of Solar Photovoltaic Panels by the Approach of Machine Learning

A further study on the scour around the monopile foundation of offshore wind turbines

Intelligent monitoring of photovoltaic panels based on infrared detection

Deep balanced cascade forest: An novel fault diagnosis method for data imbalance

Advances in Machine Condition Monitoring and Fault Diagnosis

Life-cycle assessment of the environmental impact of the batteries used in pure electric passenger cars

A Feasibility Study to Reduce Infrasound Emissions from Existing Wind Turbine Blades Using a Biomimetic Technique

A feasibility study of reducing scour around monopile foundation using a tidal current turbine

Collaborators (5)

Haiyan Miao

Mayorkinos Papaelias

João Pombo

Sadegh Nadimi

Zhiqiang Hu

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