• Proceedings of the KSPS conference
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• 2004.05a
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• pp.231-234
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• 2004

This paper describes an efficient method for improving the noise-robustness in speech recognition in a running car by considering wind noise. In driving car, mainly three kind of noises engine noise, tire noise and wind noise, are severely affect recognition performance. Especially wind noise is an important factor in driving car with window opened. We analyzed wind noise in various driving conditions that are 60, 80, 100 km/h with window fully opened, window half opened. We clarified that the recognition rate is significantly degenerated when the wind noise components in the frequency range above 200 Hz are large. We developed a preprocessing method to improve the noise robustness despite of wind noise. We adaptively changed the cutoff frequency of the front-end high-pass filter from 100 through 200 Hz according to the level of the wind noise components. By this method, the recognition rate is considerably improved for all kind of driving conditions

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2009.04a
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• pp.63-67
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• 2009

The previous work (Cheong et al., 2006) where the characteristics of acoustic emissions of wind turbines has been investigated according to the methods of power regulation, has showed that the acoustic power of wind turbine using the stall control for power regulation is more correlated with the wind speed than that using the pitch control. In this paper, basically extending this work, the noise generation characteristics of large modern upwind wind turbines are experimentally indentified according to the power regulation methods. To investigate the noise generation mechanisms, the distribution of noise sources in the rotor plane is measured by using the Beam-forming measurement system (B&K 7768, 7752, WA0890) consisting of 48 microphones. The array results for the 660 kW wind turbine show that all noise is produced during the downward movement of the blades. This result show good agreement with the theoretical result using the empirical formula with the parameters: the convective amplification; trailing edge noise directivity; flow-speed dependence. This agreement implies that the trailing edge noise is dominant over the whole frequency range of the noise from the 660 kW wind turbine using the pitch control for power regulation.

• 한국신재생에너지학회:학술대회논문집
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• 2009.11a
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• pp.465-465
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• 2009

Wind power is one of the most reliable renewable energy sources and the installed wind turbine capacities are increasing radically every year. Although wind power has been favored by the public in general, the problem with the impact of wind turbine noise on people living in the vicinity of the turbines has been increased. Low noise wind turbine design is becoming more important as noise is spreading more adverse effect of wind turbine to public. This paper demonstrates the design of 10 kW class wind turbines, each of three blades, a rotor diameter 6.4m, a rated rotating speed 200 rpm and a rated wind speed 10 m/s. The optimized airfoil is dedicated for the 75% spanwise position because the dominant source of a wind turbine blade has been known as trailing edge noise from the outer 25% of the blade. Numerical computations are performed for incompressible flow and for Mach number at 0.145 and for Reynolds numbers at $1.02{\times}10^6$ with a lift performance, which is resistant to surface contamination and turbulence intensity. The objective in the low design process is to reduce noise emission, while sustaining high aerodynamic efficiency. Dominant broadband noise sources are predicted by semi-empirical formulas composed of the groundwork by Brooks et al. and Lowson associated with typical wind turbine operation conditions. During the airfoil redesign process, the aerodynamic performance is analyzed to minimize the wind turbine power loss. The results obtained from the design process show that the design method is capable of designing airfoils with reduced noise using a commercial 10 kW class wind turbine blade airfoil as a basis. The new optimized airfoil clearly indicates reduction of total SPL about 3 dB and higher aerodynamic performance.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.11b
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• pp.166-169
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• 2005

The best sunroof wind noise quality is mainly related to the sunroof deflector which affects both low-speed buffeting and high-speed aerodynamic noise. An automatic deflector-moving and noise-measuring apparatus is developed to obtain hundreds of measuring data which haven't been available by hand. With an additional program for fast and easy noise analysis, this device leads quickly to the better position and angle of the deflector. Now, the 'better' means the lower noise level and the robuster design solution. From these kinds of better solutions, more meaningful guidelines on the deflector design and sunroof wind noise reduction can be suggested.

• New & Renewable Energy
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• v.16 no.2
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• pp.1-13
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• 2020

The reduction of noise from wind turbines has been studied using various methods. Some examples include controlling wind turbine blades, designing low-noise-emitting wind turbine blades, and using trailing-edge serrations. Among these methods, serration is considered an effective noise reduction method. Various studies have aimed to understand the effects of trailing-edge serration parameters. Most studies, however, have focused on fixed-wing concepts, and few have analyzed noise reduction or developed a prediction method for rotor-type blades. Herein, a noise prediction method, composed of two noise prediction methods for a wind turbine with trailing-edge serrations, is proposed. From the flow information obtained by an in-house program (WINFAS), the noise from non-serrated blades is calculated by turbulent ingestion noise and airfoil self-noise prediction methods. The degree of noise reduction caused by the trailing-edge serrations is predicted in the frequency domain by Lyu's method. The amount of noise reduction is subtracted from the predicted result of the non-serrated blade and the total reduction of the noise from the rotor blades is calculated.

• Wind and Structures
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• v.31 no.3
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• pp.185-196
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• 2020

A method to reduce the wind pressure at the leading edge of a noise barrier was investigated by gradually lowering the height of a member added to the end of the noise barrier. The shape of the lowered height of the added member was defined by its length and slope, and the optimal variable was determined in wind tunnel testing via the boundary-layer wind profile. The goal of the optimal shape was to reduce the wind pressure at the leading edge of the noise barrier to the level suggested in the Eurocode and to maintain the base-bending moment of the added member at the same level as the noise-barrier section. Using parametric wind tunnel investigation, an added member with a slope of 1:2 that protruded 1.2 times the height of the noise barrier was proposed. This added member is expected to simplify, or at least minimize, the types of column members required to equidistantly support both added members and noise barriers, which should thereby improve the safety and construction convenience of noise-barrier structures.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.11a
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• pp.1482-1489
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• 2007

In this paper, characteristics of infrasound and low-frequency noise emission from large modern wind turbines are experimentally investigated. The sound measurement procedures of IEC 61400-11 and ISO 7196 are utilized to field test and evaluation of noise emission from each of 1.5 MW and 660 kW wind turbines using the stall regulation and the pitch control for the power regulation, respectively. It was found that the G-weighted SPLs of low-frequency noise including infrasound shows positive correlation with the wind speeds, irrespective of methods of power regulation. This highlights the potential complaint of local community against the infrasound and low-frequency noise of wind turbines. The comparison of measured data with the existing hearing thresholds and criteria curves shows that it is highly probable that the low-frequency noise from the 1.5 MW and 660 kW wind turbines in the frequency range over 30 Hz leads to the psychological complaint of ordinary adults, and that the infrasound in the frequency range from 5 Hz to 8 Hz causes the complaint by rattling the house fitting such as doors and windows.

• Proceedings of the KIEE Conference
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• 2002.11b
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• pp.35-37
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• 2002

Most of the inhabitants living near power line complain wind noise from power line to be problems they can feel directly if there is no countermeasure to remove noise basically. Wind noise from power line happens by tower, insulators, conductor and others in their operating individually or complexly. Wind noise show us several forms like whistle, siren and bullfrog croaking as height of noise source is high and elastic wave tone with low frequency. This paper shows actual conditions and occurrence cause which may be investigated and analyzed on the wind noise, and also prepares mitigation methods and introduces a working sample to reduce a wind noise.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.10a
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• pp.431-434
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• 2014

Wind turbine industry is the most developing field among other renewable energy industry. As expanding wind farms, noise is the big problem to solve. This study is about wind turbine noise measuring method based on IEC 61400-11. Sound pressure levels, 1/3-octave band levels, and low frequency sound pressure levels of a 3 MW wind turbine were measured and analyzed.

• 한국신재생에너지학회:학술대회논문집
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• 2008.05a
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• pp.315-318
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• 2008

Numerical calculation for the 1MW class horizontal axis wind turbine blade has been carried out to estimate the magnitude between discrete noise and random noise. Farassat formula 1A was adopted to get the discrete noise signal, and blade element momentum theory was used to obtain the distribution of the aerodynamic data along the blade span. Fukano's approach was also adopted to calculate the unsteady aerodynamic random noise due to the Karman vortex generation at the trailing edge of the wind turbine blade. From the noise prediction for the 1MW class horizontal axis wind turbine, the frequency band of the discrete noise lies in the infrasound region, and that of the random noise lies in the audible band region.