scholarly journals Motion Blur Removal for Uav-Based Wind Turbine Blade Images Using Synthetic Datasets

2021 ◽  
Vol 14 (1) ◽  
pp. 87
Author(s):  
Yeping Peng ◽  
Zhen Tang ◽  
Genping Zhao ◽  
Guangzhong Cao ◽  
Chao Wu
Keyword(s):  
Wind Turbine ◽  
Turbine Blades ◽  
Synthesis Method ◽  
Motion Blur ◽  
Image Motion ◽  
Video Sequences ◽  
Synthetic Image ◽  
Motion Deblurring ◽  
Image Pairs ◽  
Blurred Images

Unmanned air vehicle (UAV) based imaging has been an attractive technology to be used for wind turbine blades (WTBs) monitoring. In such applications, image motion blur is a challenging problem which means that motion deblurring is of great significance in the monitoring of running WTBs. However, an embarrassing fact for these applications is the lack of sufficient WTB images, which should include better pairs of sharp images and blurred images captured under the same conditions for network model training. To overcome the challenge of image pair acquisition, a training sample synthesis method is proposed. Sharp images of static WTBs were first captured, and then video sequences were prepared by running WTBs at different speeds. The blurred images were identified from the video sequences and matched to the sharp images using image difference. To expand the sample dataset, rotational motion blurs were simulated on different WTBs. Synthetic image pairs were then produced by fusing sharp images and images of simulated blurs. Finally, a total of 4000 image pairs were obtained. To conduct motion deblurring, a hybrid deblurring network integrated with DeblurGAN and DeblurGANv2 was deployed. The results show that the integration of DeblurGANv2 and Inception-ResNet-v2 provides better deblurred images, in terms of both metrics of signal-to-noise ratio (80.138) and structural similarity (0.950) than those obtained from the comparable networks of DeblurGAN and MobileNet-DeblurGANv2.

scholarly journals Motion Deblurring in Image Color Enhancement by WGAN

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Jiangfan Feng ◽  
Shuang Qi
Keyword(s):  
Image Enhancement ◽  
Learning Algorithm ◽  
State Of The Art ◽  
Motion Blur ◽  
Image Motion ◽  
Generative Adversarial Networks ◽  
Target Image ◽  
Research Areas ◽  
Motion Deblurring ◽  
Color Enhancement

Motion deblurring and image enhancement are active research areas over the years. Although the CNN-based model has an advanced state of the art in motion deblurring and image enhancement, it fails to produce multitask results when challenged with the images of challenging illumination conditions. The key idea of this paper is to introduce a novel multitask learning algorithm for image motion deblurring and color enhancement, which enables us to enhance the color effect of an image while eliminating motion blur. To achieve this, we explore the synchronization of processing two tasks for the first time by using the framework of generative adversarial networks (GANs). We add L1 loss to the generator loss to simulate the model to match the target image at the pixel level. To make the generated image closer to the target image at the visual level, we also integrate perceptual style loss into generator loss. After a lot of experiments, we get an effective configuration scheme. The best model trained for about one week has achieved state-of-the-art performance in both deblurring and enhancement. Also, its image processing speed is approximately 1.75 times faster than the best competitor.

Selection of a leading edge noise prediction method for PNoise

2018 ◽  
pp. 214-223
Author(s):  
AM Faria ◽  
MM Pimenta ◽  
JY Saab Jr. ◽  
S Rodriguez
Keyword(s):  
Wind Turbine ◽  
Turbine Blades ◽  
Prediction Method ◽  
Leading Edge ◽  
Wind Farms ◽  
Broadband Noise ◽  
Turbulence Energy ◽  
Noise Prediction ◽  
Migration Routes ◽  
Turbulent Inflow

Wind energy expansion is worldwide followed by various limitations, i.e. land availability, the NIMBY (not in my backyard) attitude, interference on birds migration routes and so on. This undeniable expansion is pushing wind farms near populated areas throughout the years, where noise regulation is more stringent. That demands solutions for the wind turbine (WT) industry, in order to produce quieter WT units. Focusing in the subject of airfoil noise prediction, it can help the assessment and design of quieter wind turbine blades. Considering the airfoil noise as a composition of many sound sources, and in light of the fact that the main noise production mechanisms are the airfoil self-noise and the turbulent inflow (TI) noise, this work is concentrated on the latter. TI noise is classified as an interaction noise, produced by the turbulent inflow, incident on the airfoil leading edge (LE). Theoretical and semi-empirical methods for the TI noise prediction are already available, based on Amiet’s broadband noise theory. Analysis of many TI noise prediction methods is provided by this work in the literature review, as well as the turbulence energy spectrum modeling. This is then followed by comparison of the most reliable TI noise methodologies, qualitatively and quantitatively, with the error estimation, compared to the Ffowcs Williams-Hawkings solution for computational aeroacoustics. Basis for integration of airfoil inflow noise prediction into a wind turbine noise prediction code is the final goal of this work.

Experiments of Wind Turbine Blades with Rocket Triggered Lightning

2009 ◽  
Vol 129 (5) ◽  
pp. 689-695
Author(s):  
Masayuki Minowa ◽  
Shinichi Sumi ◽  
Masayasu Minami ◽  
Kenji Horii
Keyword(s):  
Wind Turbine ◽  
Turbine Blades ◽  
Wind Turbine Blades ◽  
Triggered Lightning

Aerodynamic Shape Influence and Optimum Thickness Distribution Analysis of Perceptive Wind Turbine Blade

2018 ◽  
Vol 7 (3) ◽  
pp. 1
Author(s):  
J. V. Muruga Lal Jeyan ◽  
Akhila Rupesh ◽  
Jency Lal
Keyword(s):  
Wind Energy ◽  
Wind Turbine ◽  
Thickness Distribution ◽  
Turbine Blades ◽  
Reduced Form ◽  
Load Factor ◽  
Strong Impact ◽  
Theory Approach ◽  
Distribution Analysis ◽  
Optimum Thickness

The aerodynamic module combines the three-dimensional nonlinear lifting surface theory approach, which provides the effective propagated incident velocity and angle of attack at the blade section separately, and a two-dimensional panel method for steady axisymmetric and non-symmetric flow has to be involved to obtain the 3D pressure and velocity distribution on the wind mill model blade. Wind mill and turbines have become an economically competitive form of efficiency and renewable work generation. In the abroad analytical studies, the wind turbine blades to be the target of technological improvements by the use of highly possible systematic , aerodynamic and design, material analysis, fabrication and testing. Wind energy is a peculiar form of reduced form of density source of power. To make wind power feasible, it is important to optimize the efficiency of converting wind energy into productivity source. Among the different aspects involved, rotor aerodynamics is a key determinant for achieving this goal. There is a tradeoff between thin airfoil and structural efficiency. Both of which have a strong impact on the cost of work generated. Hence the design and analysis process for optimum design requires determining the load factor, pressure and velocity impact and optimum thickness distribution by finding the effect of blade shape by varying thickness on the basis of both the aerodynamic output and the structural weight.

Folding of flexible hinges for aircraft wingtips and wind turbine blades

2021 ◽  
Author(s):  
Aileen G. Bowen Perez ◽  
Giovanni Zucco ◽  
Paul Weaver
Keyword(s):  
Wind Turbine ◽  
Turbine Blades ◽  
Wind Turbine Blades

Evaluation of the influence of wind speed and angle of attack on the aerodynamic effect of wind turbine blades

2017 ◽  
Author(s):  
Salete Alves ◽  
Luiz Guilherme Vieira Meira de Souza ◽  
Edália Azevedo de Faria ◽  
Maria Thereza dos Santos Silva ◽  
Ranaildo Silva
Keyword(s):  
Wind Speed ◽  
Wind Turbine ◽  
Turbine Blades ◽  
Angle Of Attack ◽  
Wind Turbine Blades ◽  
Aerodynamic Effect
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