Beyond traditional wind farm noise characterisation using transfer learning

Published Online: 10 May 2022This study proposes an approach for the characterisation and assessment of wind farm noise (WFN), which is based on extraction of acoustic features between 125 and 7500 Hz from a pretrained deep learning model (referred to as deep acoustic features). Using data measured at a variety of locations, this study shows that deep acoustic features can be linked to meaningful characteristics of the noise. This study finds that deep acoustic features can reveal an improved spatial and temporal representation of WFN compared to what is revealed using traditional spectral analysis and overall noise descriptors. These results showed that this approach is promising, and thus it could provide the basis for an improved framework for WFN assessment in the future.Phuc D. Nguyen, Kristy L. Hansen, Bastien Lechat, Branko Zajamsek, Colin Hansen, and Peter Catchesid

Establishing the acute physiological and sleep disruption characteristics of wind farm versus road traffic noise disturbances in sleep: a randomized controlled trial protocol

Advance access publication 6 September 2023Study Objectives: Despite the global expansion of wind farms, effects of wind farm noise (WFN) on sleep remain poorly understood. This protocol details a randomized controlled trial designed to compare the sleep disruption characteristics of WFN versus road traffic noise (RTN). Methods: This study was a prospective, seven night within-subjects randomized controlled in-laboratory polysomnography-based trial. Four groups of adults were recruited from; 15 s events) from sleep by each noise type with acute (20-s) and more sustained (3-min) noise exposures. Secondary analyses will compare dose–response effects of sound pressure level and noise type on EEG K-complex probabilities and quantitative EEG measures, and cardiovascular activation responses. Group effects, self-reported noise sensitivity, and wake versus sleep noise exposure effects will also be examined. Conclusions: This study will help to clarify if wind farm noise has different sleep disruption characteristics compared to road traffic noise.Gorica Micic, Branko Zajamsek, Bastien Lechat, Kristy Hansen, Hannah Scott, Barbara Toson, Tessa Liebich, Claire Dunbar, Duc Phuc Nguyen, Felix Decup, Andrew Vakulin, Nicole Lovato, Leon Lack, Colin Hansen, Dorothy Bruck, Ching Li Chai-Coetzer, Jeremy Mercer, Con Doolan and Peter Catchesid

Characterising noise and annoyance in homes near a wind farm

This study examines the relationship between indoor sound pressure level, local weather conditions, wind farm output power and resident rated annoyance in homes near a wind faun. A new methodology is presented that simultaneously records resident rated annoyance and corresponding time-series noise data while continuously monitoring one-third octave band noise levels and local weather conditions. Results of indoor noise and annoyance monitoring are presented for two homes near a wind farm whose residents claim to be annoyed by wind farm noise. Annoyance was found to be related to the overall noise level; however, noise levels were more strongly controlled by local wind speed.Zajamsek, B, Zajamsek, Branko; Moreau, DJ, Moreau, Danielle J.; Doolan, CJ, Doolan, Con J

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

DOI: 10.3397/1/376207To accurately characterise the noise measured in the vicinity of wind farms, outdoor microphones must be adequately protected from the wind. A standard 90 mm windshield is appropriate for measurements in light winds; however, as the wind speed increases, wind-induced pressure fluctuations contribute to the measured sound pressure level, leading to erroneous data. Three alternative secondary windshields have been developed and tested in an outdoor environment and evaluated for their ability to allow low frequency noise and infrasound measurements to be obtained in the presence of wind. Performance evaluation is facilitated through analysis of high resolution spectra as well as analysis of the coherence between microphones with different windshields under various meteorological conditions. This enables a distinction to be made between noise originating from sources such as a wind farm and wind-induced noise. The effect of the microphone location with respect to the ground surface has also been investigated for frequencies up to 100 Hz.Kristy Hansen, Branko Zajamšek and Colin Hanse

Numerical simulation of blade-passage noise

Numerical simulations are used to investigate the noise generated by the passage of a rotor blade past a fixed object (the blade-passage effects), which was studied by simulating a three-bladed rotor that is supported by a vertical cylindrical tower. To isolate the blade-passage effects, no incoming wind was introduced in the simulation. The symmetric blade was set to zero pitch angle relative to the plane of rotation and two blade-tower distances were investigated. The sliding mesh method was used to simulate the rotation of the blades and Curle's acoustic analogy was used to predict the noise generated from the simulated flow data. Intense force fluctuations occur during the interaction on both the tower and the passing blade, and these are the primary sources of blade-passage noise. The contribution of the force fluctuations on the support tower to blade-passage noise, which previously had been ignored, was revealed to be more significant than that of the blades. The numerical model successfully predicts the noise spectra, which are validated by the very good agreement with experimental measurements. The simulations provide a framework to better understand blade–tower interaction noise in various applications

Analysis of unweighted low frequency noise and infrasound measured at a residence in the vicinity of a wind farm

To characterise the noise at several residences located nearby a South Australian wind farm, time-data files as well as the third-octave spectra have been measured indoors and outdoors using low-frequency microphones fitted with various wind shields. Five consequative nights of data have been analysed and four cases are presented here to highlight the importance of atmospheric stability and the relative wind direction between the wind farm and a residence on the measured results. In the downwind cases, two low frequency tones were detected around 28 Hz and 46 Hz and significant levels of amplitude modulation of these tones at the blade pass frequency were observed. This amplitude modulation was most prominent when atmospheric conditions were stable. The presence of these tones and the associated amplitude modulation was also observed in the vibration results, however another amplitude modulated tone at 16 Hz was found to be more significant in terms of vibration. It was also found that low-frequency indoor noise levels varied by as much as 20dB with position in a room, due to the existence of room resonances.Kristy Hansen , Branko Zajamšek and Colin Hansenhttp://www.acoustics.asn.au/conference_proceedings/AAS2013/http://www.acoustics.asn.au/conference_proceedings/AAS2013/papers/AAS2013-Information.pd

Indoor infrasound and low-frequency noise monitoring in a rural environment

This paper presents the results of recent indoor noise monitoring test that was conducted in a room of a home near a wind farm whose resident claims to be annoyed by wind farm noise. The testing uses low-frequency microphones that can resolve noise below 0.5 Hz. The aim of the study is to examine the relationship(s) between the sound pressure level, weather conditions, resident rated annoyance to sound and wind farm output power data. The study concentrates on sound in the low and infrasonic frequency ranges. Additionally, the methodology records two-minutes of audio data at the same time a resident claim to be annoyed by noise from wind turbines. Annoyance was found to have some correlation with the overall noise level; however, noise levels are also correlated with local wind speed.Branko Zajamsek, Con Doolan, Danielle Moreau, Kristy Hansenhttp://www.acoustics.asn.au/conference_proceedings/AAS2013/http://www.acoustics.asn.au/conference_proceedings/AAS2013/papers/AAS2013-Information.pd

Subjective responses to wind farm noise: A review of laboratory listening test methods

Available online 14 August 2019Laboratory listening tests are a fundamental part of identifying and quantifying human perceptual responses to noise, including wind farm noise (WFN); a low-frequency environmental noise with time-varying components with the potential to impact more people as wind farm facilities continue to expand worldwide. Design characteristics of WFN listening tests vary between studies. This likely impacts WFN listening test results and makes quantitative comparisons difficult between studies. Accordingly, this paper reviews the available literature regarding WFN listening test methods, their overall characteristics and potentially important differences in noise stimuli and rating methods used. The key design variables explored include participant selection, stimuli duration, signal synthesis methods, noise reproduction methods and listening room characteristics. Listening test results from studies that have investigated the perceptual effects of various WFN components such as lowfrequency noise and infrasound, tonality and amplitude modulation are presented. The impact on listening tests of factors unrelated to noise such as sensory acuity and sensitivity, attitudes/beliefs and visual effects are also explored. It is shown that some WFN characteristics have received limited attention to date in listening tests. These include broadband low-frequency noise, tonal noise, tonal amplitude modulation and amplitude modulation parameters such as modulation frequency and intermittency. The relative importance of acoustic and non-acoustic factors to human perception is also largely unknown and requires well-designed listening tests to help elucidate.Mahmoud A. Alamir, Kristy L. Hansen, Branko Zajamsek, Peter Catchesid

Long-term quantification and characterisation of wind farm noise amplitude modulation

The large-scale expansion of wind farms has prompted community debate regarding adverse impacts of windfarm noise (WFN). One of the most annoying and potentially sleep disturbing components of WFN is amplitudemodulation (AM). Here we quantified and characterised AM over one year using acoustical and meteorologicaldata measured at three locations near three wind farms. We found that the diurnal variation of outdoor AMprevalence was substantial, whereby the nighttime prevalence was approximately 2 to 5 times higher thanthe daytime prevalence. On average, indoor AM occurred during the nighttime from 1.1 to 1.7 times lessoften than outdoor AM, but the indoor AM depth was higher than that measured outdoors. We observed anassociation between AM prevalence and sunset and sunrise. AM occurred more often during downwind andcrosswind conditions. These findings provide important insights into long term WFN characteristics that willhelp to inform future WFN assessment guidelines.Phuc D. Nguyen, Kristy L. Hansen, Peter Catcheside, Colin H. Hansen, Branko Zajams

Semi-empirical modelling of rotor aerodynamic noise

The trailing edge surface pressure spectrum model of Herr (2010) was used in combination with the Howe (1978) farfield propagation method to allow for variations of flow properties in the span-wise direction and for use in conjunction with modern computational fluid dynamics codes. The model was validated against experimental data from the literature. As an example application the method was used to estimate the trailing edge noise of a model wind turbine. An existing leading edge noise model used together with the trailing edge model was found to agree well with the total noise measured experimentally.J. Coombs, B. Zajamsek, C. Doolan, Z. Prime, L. Brooks, D. Moreau, A. Zande