Literature DB >> 20815449

Annoyance from industrial noise: indicators for a wide variety of industrial sources.

M Alayrac1, C Marquis-Favre, S Viollon, J Morel, G Le Nost.   

Abstract

In the study of noises generated by industrial sources, one issue is the variety of industrial noise sources and consequently the complexity of noises generated. Therefore, characterizing the environmental impact of an industrial plant requires better understanding of the noise annoyance caused by industrial noise sources. To deal with the variety of industrial sources, the proposed approach is set up by type of spectral features and based on a perceptive typology of steady and permanent industrial noises comprising six categories. For each perceptive category, listening tests based on acoustical factors are performed on noise annoyance. Various indicators are necessary to predict noise annoyance due to various industrial noise sources. Depending on the spectral features of the industrial noise sources, noise annoyance indicators are thus assessed. In case of industrial noise sources without main spectral features such as broadband noise, noise annoyance is predicted by the A-weighted sound pressure level L(Aeq) or the loudness level L(N). For industrial noises with spectral components such as low-frequency noises with a main component at 100 Hz or noises with spectral components in middle frequencies, indicators are proposed here that allow good prediction of noise annoyance by taking into account spectral features.

Mesh:

Year:  2010        PMID: 20815449     DOI: 10.1121/1.3466855

Source DB:  PubMed          Journal:  J Acoust Soc Am        ISSN: 0001-4966            Impact factor:   1.840


  3 in total

1.  An Optimization Study on Listening Experiments to Improve the Comparability of Annoyance Ratings of Noise Samples from Different Experimental Sample Sets.

Authors:  Guoqing Di; Kuanguang Lu; Xiaofan Shi
Journal:  Int J Environ Res Public Health       Date:  2018-03-08       Impact factor: 3.390

2.  A Conceptual Framework Proposal for a Noise Modelling Service for Drones in U-Space Architecture.

Authors:  Tommy Langen; Vimala Nunavath; Ole Henrik Dahle
Journal:  Int J Environ Res Public Health       Date:  2021-12-25       Impact factor: 3.390

3.  Influencing Factors Identification and Prediction of Noise Annoyance-A Case Study on Substation Noise.

Authors:  Guoqing Di; Yihang Wang; Yao Yao; Jiangang Ma; Jian Wu
Journal:  Int J Environ Res Public Health       Date:  2022-07-09       Impact factor: 4.614

  3 in total

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