Abstract
In China, noise pollution from substations in urban areas is becoming more and more serious. An annoyance evaluation of the noise emitted by urban substations is presented. First, the subjective evaluation is conducted on the noise samples from urban substations via the semantic differential method. Subsequently, according to the typical characteristics of urban substation noise, 14 acoustical metrics are used to describe the noise samples for objective evaluation. Then the correlation analysis and regression analysis between the objective and subjective evaluation results are carried out. Finally, a regression model for urban substation noise evaluation is established. Practical application shows that the regression model can correctly predict the subjective annoyance of urban substation noise.
Highlights
With the continuous and rapid progress of urbanization in China, more and more substations are being built in or near urban residential areas
Liu[12] introduced the acoustical metrics such as psychoacoustics metrics and the sound pressure level (SPL) of each octave band to establish the mean annoyance (MA) and percentage of highly annoyed (%HA) prediction model of substation noise based on logical regression and stepwise regression analysis
The sound quality assessment method is used to scientifically and reasonably investigate the annoyance of the noise emitted by an urban substation in China
Summary
With the continuous and rapid progress of urbanization in China, more and more substations are being built in or near urban residential areas. Chen et al.[11] conducted multiple linear regression analysis on substation noise samples based on currently widely used psychoacoustic metrics They established an annoyance prediction model and pointed out that the subjective annoyance mainly depends on the A-weighted sound pressure level (AWSPL). Liu[12] introduced the acoustical metrics such as psychoacoustics metrics and the sound pressure level (SPL) of each octave band to establish the mean annoyance (MA) and percentage of highly annoyed (%HA) prediction model of substation noise based on logical regression and stepwise regression analysis. We present the subjective evaluation of the noise samples of an urban substation. The standard deviation was relatively low, which means that the evaluation scores of noise samples were concentrated
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