TY - JOUR
T1 - Research on prediction and methods of evaluating sound exposure from a mixture of multiple single sources
AU - Yan, Liang
AU - Chen, Ke An
AU - Stoop, Ruedi
PY - 2014/3/5
Y1 - 2014/3/5
N2 - In this paper, the prediction and the way for calculating the total exposure level (to be denoted by LTotal) from a mixture of multiple single sources are proposed, on the premise that each single exposure level from every component single source (to be denoted by Li, where i denotes the number of single sources and i=1, 2, ⋯, K) is known. Firstly, a novel method for sound exposure level evaluation, based on a short-term exposure level in the duration of the sound event, is proposed. Using this method, each single exposure level obtained from all the single sound samples and the total exposure level obtained from every artificially combined sound samples are evaluated. Then, we lay special stress on analyzing the quantitative relationships between LTotal and Li (i=1, 2, ⋯, K) measured in three types of sound exposure indicators. All analytical results indicate that our anticipative gain of the total exposure level LTotal from a mixture of multiple single sources can be predicted on the premise that each single exposure level from every componential single source is known. To modify the predicted results, we just need to know the number of specific independent components K and the range of the single exposure levels ρ.
AB - In this paper, the prediction and the way for calculating the total exposure level (to be denoted by LTotal) from a mixture of multiple single sources are proposed, on the premise that each single exposure level from every component single source (to be denoted by Li, where i denotes the number of single sources and i=1, 2, ⋯, K) is known. Firstly, a novel method for sound exposure level evaluation, based on a short-term exposure level in the duration of the sound event, is proposed. Using this method, each single exposure level obtained from all the single sound samples and the total exposure level obtained from every artificially combined sound samples are evaluated. Then, we lay special stress on analyzing the quantitative relationships between LTotal and Li (i=1, 2, ⋯, K) measured in three types of sound exposure indicators. All analytical results indicate that our anticipative gain of the total exposure level LTotal from a mixture of multiple single sources can be predicted on the premise that each single exposure level from every componential single source is known. To modify the predicted results, we just need to know the number of specific independent components K and the range of the single exposure levels ρ.
KW - Combined source
KW - Predicting model
KW - Single source
KW - Sound exposure
UR - http://www.scopus.com/inward/record.url?scp=84896051127&partnerID=8YFLogxK
U2 - 10.7498/aps.63.054302
DO - 10.7498/aps.63.054302
M3 - 文章
AN - SCOPUS:84896051127
SN - 1000-3290
VL - 63
SP - 54302
JO - Wuli Xuebao/Acta Physica Sinica
JF - Wuli Xuebao/Acta Physica Sinica
IS - 5
ER -