Perception of low frequency components in wind turbine noise

2014 ◽  
Vol 62 (5) ◽  
pp. 295-305 ◽  
Author(s):  
Sakae Yokoyama ◽  
Shinichi Sakamoto ◽  
Hideki Tachibana
Keyword(s):  
Wind Turbine ◽  
Low Frequency ◽  
Wind Turbine Noise ◽  
Frequency Components

scholarly journals A Review of the Potential Impacts of Wind Turbine Noise in the Australian Context

2020 ◽  
Vol 48 (2) ◽  
pp. 181-197
Author(s):  
John Laurence Davy ◽  
Kym Burgemeister ◽  
David Hillman ◽  
Simon Carlile
Keyword(s):  
Wind Turbine ◽  
Wind Turbines ◽  
Management Strategies ◽  
Low Frequency ◽  
Frequency Noise ◽  
Low Frequency Noise ◽  
Sleep Health ◽  
Wind Turbine Noise ◽  
Objective Basis

Abstract This manuscript describes a range of technical deliberations undertaken by the authors during their work as members of the Australian Government’s Independent Scientific Committee on Wind Turbines. Central to these deliberations was the requirement upon the committee to improve understanding and monitoring of the potential impacts of sound from wind turbines (including low frequency and infrasound) on health and the environment. The paper examines existing wind turbine sound limits, possible perceptual and physiological effects of wind turbine noise, aspects of the effects of wind turbine sound on sleep health and quality of life, low-frequency noise limits, the concept of annoyance including alternative causes of it and the potential for it to be affected by low-frequency noise, the influence of amplitude modulation and tonality, sound measurement and analysis and management strategies. In so doing it provides an objective basis for harmonisation across Australia of provisions for siting and monitoring of wind turbines, which currently vary from state to state, contributing to contention and potential inequities between Australians, depending on their place of residence.

scholarly journals Perception of Low-Frequency Acoustic Signals by a Harbour Porpoise (Phocoena phocoena) in the Presence of Simulated Offshore Wind Turbine Noise

2007 ◽  
Vol 33 (1) ◽  
pp. 55-68 ◽  
Author(s):  
Klaus Lucke ◽  
Paul A. Lepper ◽  
Bert Hoeve ◽  
Eligius Everaarts ◽  
Niels van Elk ◽  
...  
Keyword(s):  
Wind Turbine ◽  
Low Frequency ◽  
Acoustic Signals ◽  
Harbour Porpoise ◽  
Offshore Wind ◽  
Offshore Wind Turbine ◽  
Phocoena Phocoena ◽  
Wind Turbine Noise

1.5 MW Wind Turbine Noise Measurement and Analysis of Low-Frequency Noise

2018 ◽  
Vol 14 (4) ◽  
pp. 4-13
Author(s):  
Eunkuk Son ◽  
Gwang-Se Lee ◽  
Jinjae Lee ◽  
Seungjin Kang ◽  
Sungmok Hwang ◽  
...  
Keyword(s):  
Wind Turbine ◽  
Low Frequency ◽  
Noise Measurement ◽  
Frequency Noise ◽  
Low Frequency Noise ◽  
Wind Turbine Noise ◽  
Measurement And Analysis

scholarly journals A Methodology for Assessment of Wind Turbine Noise Generation

1982 ◽  
Vol 104 (2) ◽  
pp. 112-120 ◽  
Author(s):  
N. D. Kelley ◽  
R. R. Hemphill ◽  
H. E. McKenna
Keyword(s):  
Wind Turbine ◽  
Residential Buildings ◽  
Energy Levels ◽  
Low Frequency ◽  
Joint Probability ◽  
Operating Conditions ◽  
Acoustic Energy ◽  
Wind Turbine Noise ◽  
Wide Range ◽  
Large Wind

The detailed analysis of a series of acoustic measurements taken near several large wind turbines (100 kW and above) has identified the maximum acoustic energy as being concentrated in the low-frequency audible and subaudible ranges, usually less than 100 Hz. These measurements have also shown any reported community annoyance associated with turbine operations has often been related to the degree of coherent impulsiveness present and the subsequent harmonic coupling of acoustic energy to residential structures. Thus, one technique to assess the annoyance potential of a given wind turbine design is to develop a method which quantifies this degree of impulsiveness or coherency in the radiated acoustic energy spectrum under a wide range of operating conditions. Experience has also shown the presence of annoying conditions is highly time dependent and nonstationary, and, therefore, any attempts to quantify or at least classify wind turbine designs in terms of their noise annoyance potential must be handled within the proper probabilistic framework. A technique is described which employs multidimensional, joint probability analysis to establish the expected coincidence of acoustic energy levels in a contiguous sequence of octave frequency bands which have been chosen because of their relationship to common structural resonant frequencies in residential buildings. Evidence is presented to justify the choice of these particular bands. Comparisons of the acoustic performance and an estimate of the annoyance potential of several large wind turbine designs using this technique is also discussed.

REACTIONS OF CODGADUS MORHUATO LOW- FREQUENCY SOUND RESEMBLING OFFSHORE WIND TURBINE NOISE EMISSIONS

Bioacoustics ◽  
2008 ◽  
Vol 17 (1-3) ◽  
pp. 207-209 ◽  
Author(s):  
CHRISTINA MUELLER-BLENKLE ◽  
EMMA JONES ◽  
DAVE REID ◽  
KARIN LÜDEMANN ◽  
RUDOLF KAFEMANN ◽  
...  
Keyword(s):  
Wind Turbine ◽  
Low Frequency ◽  
Offshore Wind ◽  
Offshore Wind Turbine ◽  
Wind Turbine Noise ◽  
Frequency Sound

‘Wind turbine syndrome’: fact or fiction?

2013 ◽  
Vol 127 (3) ◽  
pp. 222-226 ◽  
Author(s):  
A Farboud ◽  
R Crunkhorn ◽  
A Trinidade
Keyword(s):  
Wind Turbine ◽  
Search Engine ◽  
Noise Exposure ◽  
Low Frequency ◽  
Physiological Effect ◽  
Google Scholar ◽  
Frequency Noise ◽  
Low Frequency Noise ◽  
Wind Turbine Noise ◽  
Pubmed Database

AbstractObjective:Symptoms, including tinnitus, ear pain and vertigo, have been reported following exposure to wind turbine noise. This review addresses the effects of infrasound and low frequency noise and questions the existence of ‘wind turbine syndrome’.Design:This review is based on a search for articles published within the last 10 years, conducted using the PubMed database and Google Scholar search engine, which included in their title or abstract the terms ‘wind turbine’, ‘infrasound’ or ‘low frequency noise’.Results:There is evidence that infrasound has a physiological effect on the ear. Until this effect is fully understood, it is impossible to conclude that wind turbine noise does not cause any of the symptoms described. However, many believe that these symptoms are related largely to the stress caused by unwanted noise exposure.Conclusion:There is some evidence of symptoms in patients exposed to wind turbine noise. The effects of infrasound require further investigation.

Identification of low frequency wind turbine noise using secondary windscreens of various geometries

2014 ◽  
Vol 62 (2) ◽  
pp. 69-82 ◽  
Author(s):  
Kristy Hansen ◽  
Branko Zajamsek ◽  
Colin Hansen
Keyword(s):  
Wind Turbine ◽  
Low Frequency ◽  
Wind Turbine Noise

Simulations of high-resolution images of amorphous silicon films

1986 ◽  
Vol 44 ◽  
pp. 544-545
Author(s):  
G. Y. Fan ◽  
J. M. Cowley
Keyword(s):  
Electron Microscope ◽  
High Frequency ◽  
Fourier Transformation ◽  
Amorphous Materials ◽  
Low Frequency ◽  
Chromatic Aberration ◽  
Structure Information ◽  
Frequency Components ◽  
High Resolution Images ◽  
Spatial Frequency Spectrum

It is well known that the structure information on the specimen is not always faithfully transferred through the electron microscope. Firstly, the spatial frequency spectrum is modulated by the transfer function (TF) at the focal plane. Secondly, the spectrum suffers high frequency cut-off by the aperture (or effectively damping terms such as chromatic aberration). While these do not have essential effect on imaging crystal periodicity as long as the low order Bragg spots are inside the aperture, although the contrast may be reversed, they may change the appearance of images of amorphous materials completely. Because the spectrum of amorphous materials is continuous, modulation of it emphasizes some components while weakening others. Especially the cut-off of high frequency components, which contribute to amorphous image just as strongly as low frequency components can have a fundamental effect. This can be illustrated through computer simulation. Imaging of a whitenoise object with an electron microscope without TF limitation gives Fig. 1a, which is obtained by Fourier transformation of a constant amplitude combined with random phases generated by computer.

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