High-Resolution Structure-from-Motion for Quantitative Measurement of Leading-Edge Roughness

Nielsen, Mikkel Schou; Nikolov, Ivan Adriyanov; Kruse, Emil Krog; Garnæs, Jørgen; Madsen, Claus B.

doi:10.3390/en13153916

Cited by 6 publications

(8 citation statements)

References 55 publications

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“…One of the key topics related to this point is Leading Edge Erosion (LEE), which can result from abrasive airborne particles or weather conditions, and can impact the Annual Energy Production (AEP) of a MWscale wind turbine on the order of 5% (Langel et al, 2015). Current methods for identifying LEE involve manual (Nielsen et al, 2020) or drone-based visual inspection (Shihavuddin et al, 2019), electrical signal analysis (He et al, 2020) or vibration monitoring (Skrimpas et al, 2016), methods which either require the turbine to be shut down or are limited for continuous monitoring (Du et al, 2020). Therefore in the present work, a data-driven model is used to predict the state of degradation of the leading edge of a two-dimensional airfoil via aerodynamic pressure coefficient learning, under the influence of various uncertain inputs and parameters (see Section 4.2).…”

Section: Providing Added Value To Research and Industrymentioning

confidence: 99%

Development of a wireless, non-intrusive, MEMS-based pressure and acoustic measurement system for large-scale operating wind turbine blades

Barber¹,

Deparday²,

Marykovskiy³

et al. 2022

Preprint

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Abstract. As the wind energy industry is maturing and wind turbines are growing, there is an increasing need for cost-effective monitoring and data analysis solutions to understand the complex aerodynamic and acoustic behaviour of the flexible blades. Published measurements on operating rotor blades in real conditions are very scarce, due to the complexity of the installation and use of measurement systems. However, recent developments in electronics, wireless communication and MEMS sensors are making it possible to acquire data in a cost-effective and energy-efficient way. In this work, therefore, a cost-effective MEMS-based aerodynamic and acoustic wireless measurement system that is thin, non-intrusive, easy to install, low power, and self-sustaining is designed and tested. The results show that the system is capable of delivering relevant results continuously, although work needs to be done on calibrating and correcting the pressure signals, as well as on refining the concept for the attachment sleeve for weather protection in the field. Finally, two methods for using the measurements to provide added value to the wind energy industry are developed and demonstrated: (1) inferring local angle of attack via stagnation point detection using differential pressure sensors near the leading edge, and (2) detecting and classifying leading edge erosion using instantaneous snapshots of the measured pressure fields. On-going work involves field tests on an operating 6 kW wind turbine in Switzerland.

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Section: Providing Added Value To Research and Industrymentioning

confidence: 99%

Development of a wireless, non-intrusive, MEMS-based pressure and acoustic measurement system for large-scale operating wind turbine blades

Barber¹,

Deparday²,

Marykovskiy³

et al. 2022

Preprint

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“…The surface roughness of wind turbine blades concerns wind turbine manufacturers from the characterization of the roughness on the blade [1] to the estimation of the wind turbine aerodynamic performance [2]. In parallel, the constant strive to extract more energy from the wind have encouraged blade designers to increase the length of wind turbine blades [3].…”

Section: Introductionmentioning

confidence: 99%

Induced stalled flow due to roughness sensitivity for thick airfoils in modern wind turbines

Gutierrez

Llorente

Ragni

2022

J. Phys.: Conf. Ser.

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The mid-span region of wind turbine blades can be thickened to fulfil the structural requirements of the blade. Hence, thick airfoils, that were designed to operate at the root region of the blade, are moved to the mid-span region. This could not imply remarkable variations of the blade performance once its surface is smooth. However, the sensitivity of thick airfoils to roughness could cause significant aerodynamic impacts such as flow separation. This research aims to quantify the impact of the blade thickness, under smooth and rough conditions, in the annual energy production and the fatigue loads of the blade. Ten blade designs, linearly interpolated in thickness, are studied employing aero-elastic computations. The results reveal that the thickest blade increases the annual energy production by 5% with respect to the thinnest blade under rough conditions. Whereas this increase is less than 1% under smooth conditions. The loss of annual energy production varies with the blade thickness linearly for thin blades while it varies exponentially for thick blades up to 22%. Fatigue loads assessment confirmed a reduction of the damage equivalent load under smooth conditions, whereas the thickest blade increased it 28% under rough conditions.

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“…Both of these properties are often referred to as the ‘texture’ of the surface. While several recent studies have applied SfM for measuring surface roughness [ 10 , 11 , 12 , 22 , 23 , 24 ], quantitative studies of the influence of texture on the reconstruction accuracy are missing or provided for very specific use cases. This shows that further in-depth studies of the factors influencing the capture of micro- and macro-textures of 3D surfaces are needed.…”

Section: Introductionmentioning

confidence: 99%

“…In all cases, the comparison is limited by the measurement uncertainty in the reference model, e.g., of reference points or pre-aligned point-cloud [ 46 ]. A way to alleviate this is obtaining replicas of the surface by, e.g., replication molding and producing a highly accurate reference DEM using optical microscopy [ 23 ]. In addition, the use of 3D-printed objects allows for direct comparison of the measured geometries to the design geometry of the used CAD model [ 47 ].…”

Section: Introductionmentioning

confidence: 99%

“…Another way is power-spectral density (PSD) analysis, which gives a multi-scale quantification of the surface height variation [ 50 , 51 ]. Areal roughness parameters that describe different length scales were introduced by [ 23 ] for comparison between regions of interest in SfM and reference DEM. In addition, some studies have compared geometric measures on the object such as distances or angles [ 6 , 52 ] to the SfM point clouds.…”

Section: Introductionmentioning

confidence: 99%

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Quantifying the Influence of Surface Texture and Shape on Structure from Motion 3D Reconstructions

Nielsen¹,

Nikolov

Kruse

et al. 2022

Sensors

Self Cite

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In general, optical methods for geometrical measurements are influenced by the surface properties of the examined object. In Structure from Motion (SfM), local variations in surface color or topography are necessary for detecting feature points for point-cloud triangulation. Thus, the level of contrast or texture is important for an accurate reconstruction. However, quantitative studies of the influence of surface texture on geometrical reconstruction are largely missing. This study tries to remedy that by investigating the influence of object texture levels on reconstruction accuracy using a set of reference artifacts. The artifacts are designed with well-defined surface geometries, and quantitative metrics are introduced to evaluate the lateral resolution, vertical geometric variation, and spatial–frequency information of the reconstructions. The influence of texture level is compared to variations in capturing range. For the SfM measurements, the ContextCapture software solution and a 50 Mpx DSLR camera are used. The findings are compared to results using calibrated optical microscopes. The results show that the proposed pipeline can be used for investigating the influence of texture on SfM reconstructions. The introduced metrics allow for a quantitative comparison of the reconstructions at varying texture levels and ranges. Both range and texture level are seen to affect the reconstructed geometries although in different ways. While an increase in range at a fixed focal length reduces the spatial resolution, an insufficient texture level causes an increased noise level and may introduce errors in the reconstruction. The artifacts are designed to be easily replicable, and by providing a step-by-step procedure of our testing and comparison methodology, we hope that other researchers will make use of the proposed testing pipeline.

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High-Resolution Structure-from-Motion for Quantitative Measurement of Leading-Edge Roughness

Cited by 6 publications

References 55 publications

Development of a wireless, non-intrusive, MEMS-based pressure and acoustic measurement system for large-scale operating wind turbine blades

Development of a wireless, non-intrusive, MEMS-based pressure and acoustic measurement system for large-scale operating wind turbine blades

Induced stalled flow due to roughness sensitivity for thick airfoils in modern wind turbines

Quantifying the Influence of Surface Texture and Shape on Structure from Motion 3D Reconstructions

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