Acoustic Emissions from Wind Turbine Blades

Bhargava, Vasishta; Samala, Rahul

doi:10.5028/jatm.v11.1071

Cited by 8 publications

(3 citation statements)

References 11 publications

(30 reference statements)

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“…The naturally occurring acoustic excitation is provided by the airflow interaction with the WTB. The main mechanisms for this airflow-induced sound include turbulent boundary layer noise (trailing edge), inflow turbulence, laminar boundary layer vortex shedding, tip noise, and blade-tower interaction (Bhargava and Samala, 2019; Doolan et al, 2012; Hubbard and Shephard, 2009). This aerodynamic noise is typically broadband and distributed across the audible frequency range (Furuholm and Hultberg, 2013; Ramachandran et al, 2014), and is a function of the local wind speed (Cooper et al, 2010).…”

Section: Methodsmentioning

confidence: 99%

An unsupervised data-driven approach for wind turbine blade damage detection under passive acoustics-based excitation

Solimine

İnalpolat

2022

Wind Engineering

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Existing passive acoustics-based techniques for wind turbine blade damage detection lack the robustness and adaptability necessary for an operational implementation due to their physics- and model-based dependency. In contrast, this study develops an entirely unsupervised, data-driven damage detection technique. The novelty of the technique lies in (i) the development and comparison of spectral and cepstral-domain features for the robust characterization of the cavity-internal acoustics, (ii) the use of autoencoder networks to reduce the effects of non-stationary acoustic excitation, and (iii) the exclusion of labeled or damage-case data in the training set. The technique was successfully demonstrated on a wind turbine blade section inflicted with damage of various sizes, types, and locations, and subjected to airflow-induced passive acoustic excitation provided by a wind tunnel. Damage detection accuracy up to 99.82% was achieved for some damage types.

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Section: Methodsmentioning

confidence: 99%

An unsupervised data-driven approach for wind turbine blade damage detection under passive acoustics-based excitation

Solimine

İnalpolat

2022

Wind Engineering

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“…While the majority of research dedicated to wind turbine acoustics aims to understand the aerodynamic sound coming from the interaction of turbulent inflow and wind turbine blades, lesser work is carried out regarding tonal sound that is excited in the turbines drive train [10][11][12][13][14]. Advances in the field of broadband aerodynamic sound reveals the need to address tonal emission in the future.…”

Section: Motivationmentioning

confidence: 99%

Calculation of structure-borne sound in a direct drive wind turbine

Cardaun

Schelenz

Jacobs

et al. 2021

Forsch Ingenieurwes

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In this publication, the methods will be presented that are deployed to formulate a multi-physical system model of a direct drive wind turbine in order to calculate structure borne sound. The model includes excitation effect as well as sound radiating behaviour. The mechanical structure as a medium partner between excitation and radiation will be formulated through a multi-body simulation model in the time domain. In the multi-body simulation model, all relevant drivetrain components are considered with their structural eigenmodes in the frequency range of interest. The electromagnetic forces of the multi-pole ring generator are calculated and introduced into the mechanical structure at each stator tooth, rotor pole and various axial positions individually. Similarly, the modelling of the bearings is investigated for a range of available methods. Sound emission is evaluated at the large outer surface structures like tower, blades and nacelle cover. To minimize computational effort, the surface accelerations are not calculated for each surface node, instead a modal approach is used. Through a combination of mode shapes with mode participation factors of the respective structures, the surface accelerations can be regained during a post-processing step. Those results are used as input for airborne sound calculations. Nevertheless, the high number of modal and spatial degrees of freedom results in high computing costs.

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“…However, it is difficult to extend laboratory testing approaches to the real-time condition monitoring of blades for practical reasons. For an operating wind turbine, measurements of vibration [3], strain [4] or acoustic emission (AE) [5] of the blade are commonly used for damage detection. However, only sensors close to the damage locations can provide accurate information for the damage detection.…”

Section: Introductionmentioning

confidence: 99%

An aeroacoustics-based approach for wind turbine blade damage detection

Zhang

Avallone

Watson

2022

J. Phys.: Conf. Ser.

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In this work, aimed at the development of an aeroacoustics-based wind turbine blade damage detection approach, the noise scattered from two airfoils with damage at the trailing edge or at the leading edge is investigated. Four trailing edge cracks (with width of 0.2, 0.5, 1.0 and 2.0 mm) and four leading edge erosion configurations (consisting of gouges and delamination) are investigated for a NACA 0018 and a DU96 W180 airfoil. Experiments are carried out under clean and turbulent inflow conditions. Acoustic measurements are performed in an anechoic wind tunnel with a microphone array. The trailing edge crack causes a tonal peak at trailing-edge-thickness-based Strouhal number approximately equal to Sth ∼ 0.1 under clean and low turbulence intensity inflow conditions (e.g. ∼4% in this study). For a higher turbulence intensity (e.g., ∼7%), the tonal peaks are not detectable. For the leading edge erosion case, under clean inflow conditions and minor damage levels, the amplitudes of the harmonics in the trailing edge noise spectra increase compared with the baseline. For moderate damage levels, the harmonics on the suction side shift to higher frequencies with lower amplitudes. For the highest damage levels, only broadband characteristics are present, where low-frequency contributions increase and high-frequency contributions decrease as the damage level increases. When introducing turbulent inflow, the leading edge impingement noise level decreases at medium-high frequency (above 1000 Hz) with increasing levels of erosion.

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Acoustic Emissions from Wind Turbine Blades

Cited by 8 publications

References 11 publications

An unsupervised data-driven approach for wind turbine blade damage detection under passive acoustics-based excitation

An unsupervised data-driven approach for wind turbine blade damage detection under passive acoustics-based excitation

Calculation of structure-borne sound in a direct drive wind turbine

An aeroacoustics-based approach for wind turbine blade damage detection

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