scholarly journals Comparing sound emergence and sound pressure level as predictors of short-term annoyance from wind turbine noise

Acta Acustica ◽  
2020 ◽  
Vol 4 (3) ◽  
pp. 10
Author(s):  
Guillaume Dutilleux ◽  
Jean Fosset
Keyword(s):  
Wind Turbine ◽  
Sound Pressure Level ◽  
Sound Pressure ◽  
Pressure Level ◽  
Short Term ◽  
Limit Values ◽  
Wind Turbine Noise ◽  
Published Evidence ◽  
Sound Pressure Levels ◽  
Wind Energy Development

While most of the countries over the world rely on sound-pressure-level-based limit values to regulate wind energy development, sound emergence as defined in ISO 1996-1 is used in a few national legislations but also in international guidelines. There is however no published evidence that sound emergence is a relevant noise descriptor for that kind of source, namely that there is a correlation between this metric and perception or annoyance. A listening test was carried out to evaluate the relative merits of sound pressure level and sound emergence as predictors of annoyance from wind turbine noise. The test samples consisted of 45 30-s wind turbine sounds at three different A-weighted sound pressure levels and five different signal-to-noise ratios. Thirty two persons rated the test samples according to the ISO 15666 standard scale in a dry room equipped with loudspeakers. The results indicate that short term annoyance is better predicted by A-weighted sound pressure levels than by sound emergence. It is also observed that sound emergence is a poor predictor of the audibility of wind turbine sounds.

Amplitude modulations increase annoyance due to wind turbine noise immission

2021 ◽  
Vol 263 (2) ◽  
pp. 4048-4057
Author(s):  
Christoph Pörschmann ◽  
Stephan Großarth ◽  
Johannes M. Arend ◽  
Sebastian Schmitter ◽  
Dirk Schreckenberg ◽  
...  
Keyword(s):  
Wind Turbine ◽  
Wind Turbines ◽  
Current Literature ◽  
Sound Pressure Level ◽  
Sound Pressure ◽  
Pressure Level ◽  
Wind Turbine Noise ◽  
Control Location ◽  
Noise Characteristics ◽  
Study Sites

Current literature suggests that annoyance of wind turbine noise is strongly affected by amplitude modulations (AM). A survey was carried out at five German residential study sites near wind turbines with a total of about 500 residents to study the effects of AM in more detail. Annoyance, disturbances, and the perception of wind turbine noise characteristics, including AM, were assessed. For each participant, address-related exposure to rating levels of wind turbines was estimated. Further, we carried out headphone-based listening experiments with participants from three of the five study areas and with non-exposed participants from another 'control' location. In the listening experiments, perceived annoyance was rated for varying AM and for different A-weighted sound pressure levels for a total number of 79 subjects. As expected, the results show an increase in annoyance with sound pressure level. Furthermore, annoyance increased significantly with the extent of amplitude modulations. Interestingly, annoyance showed a strong rise as soon as amplitude modulations became audible in the signal and this rise was hardly affected by the sound pressure level. In our contribution, we present comparisons of the results of the survey and the listening experiments.

scholarly journals Investigation of Noise Pollution Distribution in Different Parts of Yazd Textile Factories

2021 ◽  
Author(s):  
Mohammad Javad Zare Sakhvidi ◽  
Hamideh Bidel ◽  
Ahmad Ali Kheirandish
Keyword(s):  
Occupational Exposure ◽  
Sound Pressure Level ◽  
Textile Industry ◽  
Sound Pressure ◽  
Noise Pollution ◽  
Sound Level ◽  
Pressure Level ◽  
Cross Sectional ◽  
Sound Pressure Levels ◽  
Different Parts

 Background: Chronic occupational exposure to noise is an unavoidable reality in the country's textile industry and even other countries. The aim of this study was to compare the sound pressure level in different parts of the textile industry in Yazd and in different parts of the textile industry. Methods: This cross-sectional study was performed on 930 textile workers in Yazd. A questionnaire was used to obtain demographic information and how to use protective equipment. Then, to obtain the sound pressure level of each unit and device and to use the measurement principles, a calibrated sound level meter was used. Then the results were analyzed using SPSS Ver.29 software. Results: The participants in this study were 714 males and 216 females with a mean age of 35.27 and 33.63 years, respectively. Seven hundred fifty-six participants (81.29%) were exposed to sound pressure levels higher than 85 dB. Among the participants, only 18.39% of the people used a protective phone permanently. Except for factory E, with an average sound pressure level of 77.78 dB, the rest of the factories had an average sound pressure level higher than the occupational exposure limit. The sound measurement results of different devices show that the sound pressure levels above 90 dB are related to the parts of Dolatab, Ring, Kinetting (knitting), Chanel, Autoconer, Dolakni, Open End, MultiLakni, Tabandegi, Texture, and Poy. Conclusion: Based on the results of the present study, noise above 90 dB is considered as one of the main risk factors in most parts of the textile industry (spinning and weaving), which in the absence of engineering, managerial or individual controls on it causes hearing loss in becoming employees of this industry

scholarly journals Wind turbine sound pressure level calculations at dwellings

2016 ◽  
Vol 139 (3) ◽  
pp. 1436-1442 ◽  
Author(s):  
Stephen E. Keith ◽  
Katya Feder ◽  
Sonia A. Voicescu ◽  
Victor Soukhovtsev ◽  
Allison Denning ◽  
...  
Keyword(s):  
Wind Turbine ◽  
Sound Pressure Level ◽  
Sound Pressure ◽  
Pressure Level

Variation in vibro-acoustic noise due to the defects in an automotive drum brake

2021 ◽  
Vol 263 (4) ◽  
pp. 2646-2653
Author(s):  
Ananthapadmanabhan Ramesh ◽  
Sundar Sriram
Keyword(s):  
Analytical Model ◽  
Sound Pressure Level ◽  
Sound Pressure ◽  
Transfer Functions ◽  
Acoustic Noise ◽  
Pressure Level ◽  
Acoustic Model ◽  
Drum Brake ◽  
Non Linear ◽  
Sound Pressure Levels

Drum brakes are significant contributors to noise and vibration in automobiles causing discomfort to the passengers. The vibration and hence the resulting noise increase due to various inherent defects in the drum brake, such as asymmetry. This work aims to quantify the variation in the vibro-acoustic noise due to several common defects in the drum brake using an integrated non-linear vibration analytical model and a numerical acoustic model. The sources of vibro-acoustic noise sources such as contact and reaction forces are predicted using a four-degree-of-freedom non-linear contact mechanics based analytical model. A finite element based acoustic model of the drum brake is utilized to predict the force to the sound pressure transfer function in the drum brake. Product of the transfer functions and the forces gives the corresponding sound pressure level from which the overall sound pressure levels are estimated. The variation in the overall sound pressure levels due to different drum brake defects is evaluated by introducing defects to the analytical model. The results show that the overall sound pressure level is a strong function of the defects. It is envisioned that the current work will help in the development of effective health monitoring systems.

scholarly journals Sound Levels Forecasting in an Acoustic Sensor Network Using a Deep Neural Network

Sensors ◽  
2020 ◽  
Vol 20 (3) ◽  
pp. 903 ◽  
Author(s):  
Juan M. Navarro ◽  
Raquel Martínez-España ◽  
Andrés Bueno-Crespo ◽  
Ramón Martínez ◽  
José M. Cecilia
Keyword(s):  
Neural Network ◽  
Sensor Network ◽  
Sound Pressure Level ◽  
Deep Neural Network ◽  
Sound Pressure ◽  
Noise Pollution ◽  
Pressure Level ◽  
Acoustic Sensor ◽  
Short Term ◽  
Sound Levels

Wireless acoustic sensor networks are nowadays an essential tool for noise pollution monitoring and managing in cities. The increased computing capacity of the nodes that create the network is allowing the addition of processing algorithms and artificial intelligence that provide more information about the sound sources and environment, e.g., detect sound events or calculate loudness. Several models to predict sound pressure levels in cities are available, mainly road, railway and aerial traffic noise. However, these models are mostly based in auxiliary data, e.g., vehicles flow or street geometry, and predict equivalent levels for a temporal long-term. Therefore, forecasting of temporal short-term sound levels could be a helpful tool for urban planners and managers. In this work, a Long Short-Term Memory (LSTM) deep neural network technique is proposed to model temporal behavior of sound levels at a certain location, both sound pressure level and loudness level, in order to predict near-time future values. The proposed technique can be trained for and integrated in every node of a sensor network to provide novel functionalities, e.g., a method of early warning against noise pollution and of backup in case of node or network malfunction. To validate this approach, one-minute period equivalent sound levels, captured in a two-month measurement campaign by a node of a deployed network of acoustic sensors, have been used to train it and to obtain different forecasting models. Assessments of the developed LSTM models and Auto regressive integrated moving average models were performed to predict sound levels for several time periods, from 1 to 60 min. Comparison of the results show that the LSTM models outperform the statistics-based models. In general, the LSTM models achieve a prediction of values with a mean square error less than 4.3 dB for sound pressure level and less than 2 phons for loudness. Moreover, the goodness of fit of the LSTM models and the behavior pattern of the data in terms of prediction of sound levels are satisfactory.

Gyro Rock Crusher and Asphalt Plant Sound Power Levels

2012 ◽  
Author(s):  
Henry A. Scarton ◽  
Kyle R. Wilt
Keyword(s):  
Sound Pressure Level ◽  
Sound Pressure ◽  
Low Frequency ◽  
Pressure Level ◽  
Sound Power ◽  
Far Field ◽  
Atmospheric Attenuation ◽  
Frequency Sound ◽  
Sound Pressure Levels ◽  
Rock Crusher

Sound power levels including the distribution into octaves from a large 149 kW (200 horsepower) gyro rock crusher and separate asphalt plant are presented. These NIST-traceable data are needed for estimating sound pressure levels at large distances (such as occurs on adjoining property to a quarry) where atmospheric attenuation may be significant for the higher frequencies. Included are examples of the computed A-weighted sound pressure levels at a distance from the source, including atmospheric attenuation. Substantial low-frequency sound power levels are noted which are greatly reduced in the far-field A-weighted sound pressure level calculations.

scholarly journals Noise Emissions in Milking Parlours with Various Construction Solutions

2016 ◽  
Vol 19 (2) ◽  
pp. 49-51
Author(s):  
Marie Šístková ◽  
Martin Pšenka ◽  
Ivo Celjak ◽  
Petr Bartoš ◽  
Štefan Mihina ◽  
...  
Keyword(s):  
Dairy Cows ◽  
Sound Pressure Level ◽  
Sound Pressure ◽  
Noise Exposure ◽  
Pressure Level ◽  
Different Types ◽  
Sound Pressure Levels ◽  
Mechanical Devices

Abstract Mechanical devices in parlours are a source of noise, and this noise has an effect not only on the operators of the parlour but also on dairy cows. They have more sensitive hearing than humans. The aim of this article was to analyse the sound pressure level and determine the noise exposure of dairy cows at different technological solutions of milking parlours, during their day routine. In the experiment, tandem, herringbone and rotary milking parlours were used. Noise exposure was measured during the milking process. After evaluation of noise pressure levels of different types of milking parlours, it can be concluded that in this experiment, the equivalent noise pressure level was lowest in the tandem milking parlour. Equivalent sound pressure levels in the rotary and herringbone milking parlour were almost about the same values. These values are higher than values in the tandem milking parlour, about 10 decibels. The differences within mean LAFeq values between the herringbone milking parlour and tandem milking parlour were highly statistically significant (P <0.001***).

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