某高架城际铁路近场环境噪声的心理声学评价指标研究 |
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作者单位: | ;1.西南交通大学高速铁路线路工程教育部重点实验室;2.西南交通大学土木工程学院 |
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摘 要: | 为了研究高架城际铁路环境噪声客观物理特征与人的主观感受的关系,对某城际列车高架桥段近场环境噪声进行现场测试和评价分析。通过噪声数据的频域分布,分析各测点环境噪声的主要成分,其中噪声峰值频率主要为40Hz和315Hz。分别采用A计权声压级和心理声学指标对各测点噪声进行分析和评价,采用线性回归方法分析主观烦恼度与A计权声压级和其他心理声学参数之间的相关度,发现低频噪声的A计权声压级与主观烦恼度无线性关系,而高频噪声的相关度较好,验证了A计权声压级评价低频噪声的不可靠性。结果表明:当环境噪声主要成分为低频噪声时,尖锐度是最优心理声学评价指标;当环境噪声主要成分为高频噪声时,总响度是最优心理声学评价指标。
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关 键 词: | 环境噪声 城际铁路 频谱分析 心理声学参数 线性回归 |
Psychoacoustic Evaluation Index of Near-field Environmental Noise in an Intercity Railway |
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Institution: | ,Key Laboratory of High-speed Railway Engineering,Ministry of Education,Southwest Jiaotong University,School of Civil Engineering,Southwest Jiaotong University |
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Abstract: | In order to study the relationship between objective physical characters and subjective feeling subject to environmental noise in the intercity railway,the surrounding environment noise in the viaduct section of an intercity train line is studied based on evaluation analysis and field tests.Through frequency domain distribution of noise data,the main components of environmental noise at each measurement point are analyzed,and the peak frequencies of noise are mainly 40 Hz and 315 Hz.The correlation between subjective annoyance index and A-weighting sound-pressure level and other psychoacoustic parameters are analyzed by linear regression method.It is found that there is no linear relationship between the Aweighted sound pressure level of the low-frequency noise and the subjective annoyance,and the correlation of the high-frequency noise is better,and the unreliability of the low frequency noise is verified by the A-weighted sound pressure level.Research results show that when the main component of environmental noise is low-frequency noise,the sharpness is the optimal psychoacoustic evaluation index;when the main component of environmental noise is high-frequency noise,the total loudness is the optimal psychoacoustic evaluation index. |
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Keywords: | Environment noise Intercity railway Spectrum analysis Psychoacoustic parameter Linear regression |
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