Microphone-array processing for wind-tunnel measurements with strong background noise

Koop, Lars; Ehrenfried, Klaus

doi:10.2514/6.2008-2907

Cited by 42 publications

(21 citation statements)

References 12 publications

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“…Downward-passing blade noise is dominant for the majority of data, similar to the results of Oerlemans [2,3], and attributed to convective amplification and source directivity of trailing-edge noise. Application of the convective correction algorithm improves results for trailing-edge noise, as shown in Figure 12.…”

Section: Data Acquisition Campaignsupporting

confidence: 64%

“…The software compensates for the effects of sound convection by assuming a constant, identical wind speed and direction between the microphone and scan location, as in [2,3] and based on the geometrical convection analysis of Soderman et al [9] extended to three dimensions. The merit of this method was tested and is discussed in Section 4.2.…”

Section: Data Acquisition and Beamforming Softwarementioning

confidence: 99%

“…The arrays rely on signals from multiple microphones to deduce these spatial characteristics. Arrays have been used both in wind tunnels [1,2] and in the field [3,4] for measurements of noise from locomotives, airfoils, aircraft, and aircraft subsystems. However, relatively few studies have been conducted using these devices for measurements of wind turbine noise, particularly on full-scale turbines.…”

Section: Introductionmentioning

confidence: 99%

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Acoustic Array Development for Wind Turbine Noise Characterization

Buck¹,

Roadman²,

Moriarty³

et al. 2013

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Printed on paper containing at least 50% wastepaper, including 10% post consumer waste. iv AcknowledgmentsThe acoustic array design and testing team would like to acknowledge Scott Wilde and his operations team for their support in setting up, testing, and maintaining our equipment. Arlinda Huskey's help in supporting the program's logistics is much appreciated. Andy Scholbrock has been invaluable in coordinating availability of the Controls Advanced Research Turbine (CART)-2. Mike Asheim's input in array design, construction, and associated acoustic testing was also very useful. Finally, the project would not have been possible without the cooperation of the University of Colorado Boulder, their facilities, and the education they provide. Executive SummaryA prototype acoustic array for measurement of wind turbine noise has been designed in a collaborative effort by the National Renewable Energy Laboratory (NREL) and University of Colorado Boulder. The array is built upon 63 electret condenser microphones in a multi-arm logarithmic spiral pattern, a single calibrated B&K precision condenser microphone, in-house designed analog electronics, and an integrated National Instruments (NI) data acquisition system (DAS). Noise source maps are generated using a delay-and-sum beamforming algorithm with diagonal elimination in the cross-spectral matrix. The uniqueness of this array design over currently available commercial products is a lower frequency range, a weather-proof design allowing for long-term observational campaigns, and the ability to collapse and package the array for ease of transport.After an initial deployment at the Northwind 100A research turbine site for system testing, the array was deployed in late 2012 at the upwind side of the Controls Advanced Research Turbine (CART)-2 at the National Wind Technology Center (NWTC). The turbine has a highly instrumented rotor and accompanying meteorological tower enabling noise correlations with both detailed turbine operational characteristics and atmospheric conditions. An active acoustic source has been used to calibrate the array and characterize its performance. Simulated pointsource data have been used to compare these results to expected results. The array is shown to have a 3-dB beamwidth of 3.53 meters for a 750-Hz source at the center of the rotor, 56 meters from the center of the array. Turbine noise data have been collected over a range of operational conditions, including wind speeds from 7 to 22 m/s and rotor speeds of up to 42 rpm (6-second averages). Data from these measurement campaigns have been analyzed at frequencies from 750 Hz to 8 kHz.The array in its current configuration has shown point-source localization accuracy on the order of a few tens of centimeters. However, a non-negligible variation in source location under various atmospheric conditions has also been observed. Compensation for sound convection using a simplified atmospheric model in the beam-forming algorithm improved the initial results but only approximately half of the positi...

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Section: Data Acquisition Campaignsupporting

confidence: 64%

Section: Data Acquisition and Beamforming Softwarementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Acoustic Array Development for Wind Turbine Noise Characterization

Buck¹,

Roadman²,

Moriarty³

et al. 2013

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show abstract

“…For example, Michel et al 1,2 investigated airframe and engine noise of the aircraft by use of a linear and a two-dimensional microphone array. Hiroki, Koop, Finez and Humphreys [3][4][5][6] applied different type of array in wind tunnel testing recently. Siller et al 7,8 analyzed the sound sources of an Airbus 319 and a Boeing 747 in fly-over test with an array measurement system developed by DLR.…”

Section: Introductionmentioning

confidence: 99%

An Investigation of the Inlet and Exhaust Noise Sources of Turbofan Using Linear Microphone Array

Qiao

Zhao

et al. 2013

19th AIAA/CEAS Aeroacoustics Conference

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This paper presents noise source location results for a turbofan engine with the bypass ratio of 2.4 obtained from engine static test, in which the engine was installed on aircraft. Source location data from this test was used to develop engine inlet sound absorbing liner and to design the aircraft fuselage sound insulation device. A linear array of 32 microphones was used in this program to determine the jet noise source distribution for the exhaust and the fan noise from inlet. Aeroacoustic beamforming with the delay and sum scheme in time domain was modified using the DAMAS deconvolution algorithm. Data were obtained for the engine power setting which is from 60% to 90% of the design power. It was shown that the noise source was one centralized source from engine inlet, and the location of this centralized source was almost immobile. The multiple sources were also detected in exhaust noise, and the location of distributed source was moving backward with the increase of engine power(that is with the increase of jet velocity). The haymow spectrum was observed for the exhaust noise, and obvious tone noise was observed in the spectrum of inlet noise.

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“…Thus, the noise cannot be cancelled out, but it may be reduced, in an average sense, using the statistics of the signal and the noise process. In other situations, it is not possible to get a noise reference: the reference signal can either be generated artificially or extracted from the primary signal or from the imaging results [18].…”

Section: Introductionmentioning

confidence: 99%

Spectral estimation method for noisy data using a noise reference

Blacodon

2011

Applied Acoustics

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The development of array processing methods to extract the useful characteristics of acoustic sources such as their locations and absolute levels, starting from the measured sound field is one of the main issues in aero-acoustics. Generally, the methods are based on a deconvolution operation to remove the undesirable effects of smearing produced by array response. This process should be carried out after the additive noise has been suitably attenuated and, ideally, the deconvolution operator should amplify the noise as little as possible. We show that when a reference of noise is known beforehand, and under certain assumptions, that it is possible both to remove the smearing effect produced by array response and to reduce the noise contamination of the results using a method called Spectral Estimation Method With Additive Noise. This method has been applied to computer and experimental simulations involving acoustic sources radiating in a noisy environment. The levels of the sources were found with a good accuracy and the background noise highly reduced, confirming the validity of the approach and the good performance of the proposed method.

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Microphone-array processing for wind-tunnel measurements with strong background noise

Cited by 42 publications

References 12 publications

Acoustic Array Development for Wind Turbine Noise Characterization

Acoustic Array Development for Wind Turbine Noise Characterization

An Investigation of the Inlet and Exhaust Noise Sources of Turbofan Using Linear Microphone Array

Spectral estimation method for noisy data using a noise reference

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