@article {GUILLAUME:2024:0736-2935:806,
title = "Development and distribution of an in situ experimental wind turbine noise database",
journal = "INTER-NOISE and NOISE-CON Congress and Conference Proceedings",
parent_itemid = "infobike://ince/incecp",
publishercode ="ince",
year = "2024",
volume = "270",
number = "11",
publication date ="2024-10-04T00:00:00",
pages = "806-815",
itemtype = "ARTICLE",
issn = "0736-2935",
url = "https://ince.publisher.ingentaconnect.com/content/ince/incecp/2024/00000270/00000011/art00090",
doi = "doi:10.3397/IN_2024_2658",
author = "GUILLAUME, Gwena{\"e}l and COTT{\’e}, Benjamin and ECOTI{\‘e}RE, David and GAUVREAU, Benoit and LEF{\‘e}VRE, Hubert and JUNKER, Fabrice and SCHMICH-YAMANE, Isabelle",
abstract = "The PIBE project is the first French collaborative research project on wind turbine noise. One of its objectives is to quantify the experimental dispersion observed in situ on acoustic quantities/metrics and influencing parameters, and to compare it with the numerical dispersion estimated
using acoustic propagation models. A long-term experimental campaign was carried out over consecutive 410 days around a wind farm comprising eight 80-metre-high and 90-metre diameter turbines. Acoustic sensors (five Class I sound level meters) were deployed on site, recording third-octave
spectra and overall A- and Z-weighted values of the Leq indicator and fractile indices (L10, L50 and L90), at distances from 325 m to 1400 m from the wind turbines row. In addition, three 3D ultrasonic anemometers and a Lidar system were used to measure meteorological variables influencing
long-range sound propagation (e.g. wind and temperature verical profiles). Besides, train and aircraft passing close to the site were inventoried to identify periods of high background noise. All experimental data have been processed into an ElasticSearch database. An interactive web application
has been developed in R Shiny to facilitate processing, visualization and analysis of the experimental database.",
}