Acoustic Emissions from Wind Turbine Blades

Bhargava, Vasishta; Samala, Rahul

doi:10.5028/jatm.v11.1071

Cited by 9 publications

(5 citation statements)

References 11 publications

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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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“…Good agreement with experimental results from full-scale WTs has been reported by several researchers. For instance, Bhargava et al [20] verified their potential to reproduce the experimental data from a Siemens SWT-93 WT. This method was then applied to a Siemens SWT-108 WT by Buck et al [21] by using a flat plate analytical model and a correction for limited airfoil thickness.…”

Section: Introductionmentioning

confidence: 96%

Surrogate Modeling of the Aeroacoustics of an NM80 Wind Turbine

De Girolamo,

Tieghi,

Delibra

et al. 2023

IJTPP

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Wind turbines play a major role in the European Green Deal for clean energy transition. Noise is a critical aspect among open technological issues, as it determines the possibility of onshore installations near inhabited places and the possible detrimental effects on wildlife when offshore. This paper assesses the accuracy of different approaches to predicting the sound pressure level (SPL) of a wind turbine. The 2.75 MW Neg Micon NM80 horizontal axis wind turbine (HWAT) was simulated in OpenFOAM, modeling the turbine with the actuator line method (ALM) implemented in the turbinesFoam library. Two different inflow conditions were considered: a stationary inflow with a typical atmospheric boundary layer profile and a time-dependent inflow derived from a precursor channel with fully turbulent conditions. The surrogate model for noise prediction used for this work is based on the synthetic/surrogate acoustics models (SAMs) of Amiet and Brooks-Pope-Marcolini (BPM). This approach allows for blade motion modeling and the prediction of the SPL of the URANS postprocessing results. The SPL spectrum obtained was then compared to the results from the other aeroacoustic solvers of IEA Task 39 participants, showing the best performance in the fully turbulent case. The results demonstrate that coupling between the ALM and surrogate acoustics provides more accurate results than the blade element momentum (BEM) approach.

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Acoustic Emissions from Wind Turbine Blades

Cited by 9 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

Surrogate Modeling of the Aeroacoustics of an NM80 Wind Turbine

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