Study of ice accretion on wind turbine blade profiles using thermal infrared imaging

Yousuf, Adeel; Jin, Jia Yi; Sokolov, Pavlo; Virk, Muhammad Shakeel

doi:10.1177/0309524x20933948

Cited by 10 publications

(3 citation statements)

References 11 publications

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“…The results showed that the method can detect icing events with high resolution, high precision and high discrimination, accurately measure and identify the icing with a thickness of 0.1 mm, and give a timely warning in the early stage of icing. There are some studies that have used capacitive and resistance sensing technology to measure icing thickness [77,78]. The icing thickness is measured based on changes in capacitance and resistance due to icing accumulation between two charged cylindrical probes or parallel plate capacitors.…”

Section: Icing Monitoring and Safety Status Assessmentmentioning

confidence: 99%

A Review of Wind Turbine Icing and Anti/De-Icing Technologies

Zhang,

Zhang

et al. 2024

Energies

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The development and utilization of clean energy is becoming more extensive, and wind power generation is one of the key points of this. Occasionally, wind turbines are faced with various extreme environmental impacts such as icing, lightning strikes and so on. In particular, the icing of wind turbines increases icing–wind loads, and results in a reduced power output. And blades broken down lead to large-area shutdown accidents caused by high-speed rotating, which seriously affects the reliability and equipment safety of wind power generation. Relevant institutions and researchers at home and abroad have carried out a lot of research on this. This paper summarizes the formation and influencing factors of wind turbine icing, the influence of icing on wind power generation, and defense technologies. First, it introduces the formation conditions and mechanisms of icing in wind farm regions and the relationship between meteorological and climatic characteristics and icing, and analyzes the key influence factors on icing. Then, the impact of icing on wind turbines is explained from the aspects of mechanical operation, the power curve, jeopardies and economic benefits. And then the monitoring and safety status of wind turbines icing is analyzed, which involves collecting the relevant research on anti-de-icing in wind power generation, introducing various anti/de-icing technologies, and analyzing the principle of icing defense. Finally, this paper summarizes wind turbine icing and its defense technologies, and puts forward the future research direction based on the existing problems of wind power generation icing.

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Section: Icing Monitoring and Safety Status Assessmentmentioning

confidence: 99%

A Review of Wind Turbine Icing and Anti/De-Icing Technologies

Zhang,

Zhang

et al. 2024

Energies

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“…They also simulated the effect of surface dust accumulation on IRT measurements. Yousuf et al (Yousuf et al, 2021) studied ice accretion on wind turbine blades using FLIR® A615 thermal infrared camera to analyze the effect of liquid water content, angle of attack, temperature and blades profile geometry on ice formation.…”

Section: Infrared Ice-detectionmentioning

confidence: 99%

Conceptual Design of Cost-Effective Ice Detection System Based on Infrared Thermography

Yousuf¹,

Khawaja²,

Virk³

2023

Preprint

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“…Researchers are currently working on the recognition of ice accretion by infrared thermal imaging, which extracts the shape of ice accretion based on temperature differences between ice and substrate [16][17][18][19][20]. However, a challenge remains the exploration of the relationship between temperature and ice thickness using infrared thermal images, which has made some progress in marine research.…”

Section: Introductionmentioning

confidence: 99%

Ice accretion thickness prediction using flash infrared thermal imaging and BP neural networks

Lü

Qingying

Pan

et al. 2022

IET Image Processing

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The present study investigated ice accretion thickness under non-incoming flow icing conditions on the ground using an infrared thermography system that converts infrared radiation temperature. Two back propagation (BP) neural network models were developed to measure ice thickness. Both theoretical model and polynomials were employed to fit the icing surface temperature elevation sequence to extract the pixel-level temperature attenuation characteristics, which were served as the input to the BP neural networks. The prediction method of ice thickness by the BP neural network was analysed from three perspectives of sensitivity, dimension, and precision. In addition, K-nearest neighbour (KNN) and support vector regression (SVR) algorithms were compared with BP neural network. In terms of prediction effect, the BP neural network performed the best. The verification of the BP neural network based on the characteristics of the theoretical model proved that the method can effectively predict the thickness of ice accretion, and its prediction error does not exceed 10%.

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Study of ice accretion on wind turbine blade profiles using thermal infrared imaging

Cited by 10 publications

References 11 publications

A Review of Wind Turbine Icing and Anti/De-Icing Technologies

A Review of Wind Turbine Icing and Anti/De-Icing Technologies

Conceptual Design of Cost-Effective Ice Detection System Based on Infrared Thermography

Ice accretion thickness prediction using flash infrared thermal imaging and BP neural networks

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