›› 2010, Vol. 30 ›› Issue (4): 133-137.DOI: 10.3969/j.issn.1006-1355.2010.04.035

• 振动噪声测试技术 • Previous Articles     Next Articles

《Study on Noise Prediction Model of Weining Railway Section in NeijiangKunming Line》

DAI Ben-lin1,2,3,HUA Zulin1,2,3,HE Yu-long4,LI Wei3,GU Li3   

  1. (1. Key Laboratory of Integrated Regulation and Resource Development on Shallow Lake of Ministry of Education, Hohai University, Nanjing 210098, China；2. National Engineering Research Center of Water Resources Efficient Utilization and Engineering Safety, Hohai University, Nanjing 210098, China；3. College of Environmental Science and Engineering, Hohai University, Nanjing 210098, China；4. College of Environmental Science and Engineering, Southwest Jiaotong University, Chengdu 610031, China)
  • Received:2008-09-25 Revised:1900-01-01 Online:2010-08-18 Published:2010-08-18
  • Contact: DAI Ben-lin

《内昆线威宁段铁路噪声预测模式研究》

戴本林1,2,3, 华祖林1,2,3, 贺玉龙4,李伟3,顾莉3   

  1. （1.河海大学教育部浅水湖泊综合治理与资源开发重点实验室,南京210098；2.河海大学水资源高效利用与工程安全国家工程研究中心,南京210098；3.河海大学环境科学与工程学院,南京210098；4.西南交通大学环境科学与工程学院,成都610031）
  • 通讯作者: 戴本林

Abstract: Due to the requirement of railway noise evaluation, the Germany Schall03 noise forecasting model is amended according to the actual railroad situation in the western mountain areas of our country. The amended Germany Schall03 forecasting model is then used to forecast the railway noise in Weining section of NeijiangKunming line. Comparing the predictive value with the measured data, it shows that using the amended model to predict the noise of this railway section is feasible and effective. The work in this paper complements the deficiency of the research of railway noise prediction in the western mountain area of our country.

Key words: acoustics, the Schall03 model, railway noise, calculation, NeijiangKunming railway

摘要： 针对我国西部山区铁路沿线噪声预测方法研究的不足，在基于德国Schall03预测模式的基础上，为满足铁路噪声评价的要求，根据西部山区铁路实际情况，对其进行修正。用建立的德国Schall03修正模式对内昆线威宁段火车通过时的受声点噪声值进行预测，将得到的预测值与实测数据进行对比分析。结果表明，该修正模式用来预测该段铁路噪声是可行和有效的。

关键词: 声学, Schall03模式, 铁路噪声, 计算, 内昆铁路

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