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高速铁路桥梁结构噪声的全频段预测研究(Ⅰ):理论模型 被引量:25

Prediction of Structure-borne Noise of High-speed Railway Bridges in Whole Frequency Bands(Part Ⅰ):Theoretical Model
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摘要 基于车-线-桥空间耦合振动和稳态声辐射的边界元法、统计能量法理论,提出高速铁路桥梁结构噪声全频段预测方法。根据桥梁结构形式,考虑计算规模和效率,确定分析频段限,将整个频域划分为2部分;在不同的频段建立直接/间接边界元和统计能量模型,采用"强耦合"假设简化子系统耦合损耗因子求解;进行车-线-桥空间耦合振动分析,分别计算桥梁和钢轨振动响应作为边界元模型边界输入和统计能量模型能量输入,在不同频段进行稳态声辐射分析,得到桥梁结构噪声全频段结果。并对分析频段划分、边界元法边界输入、"强耦合"假设的验证、统计能量法的能量输入,声反射和声衍射处理等进行探讨。 On the basis of the theory of train-track-bridge spatial coupling vibration and steady-state acoustic ra- diation of boundary element method (BEM) and statistical energy analysis (SEA), this paper presented the method for prediction of structure-borne noise of high-speed railway Bridges in whole frequency bands. Firstly, an appropriate frequency limit was determined and the whole frequency band was divided into two parts, con- sidering the calculation scale and efficiency according to the bridge type. Then, the direct/indirect boundary el- ement and statisticM energy models were established in different frequency bands respectively. In the statistical energy model, a "strong coupling" assumption was introduced to simplify the solution of coupling loss factors between subsystems. Finally, the train-track-bridge spatial coupling vibration analysis was conducted to calcu- late the vibration responses of bridges and rails for the boundary input to the boundary element model and the energy input to the statistical energy model respectively. The frequency band division, boundary input to the boundary element model, validation of "strong coupling" assumption, energy input to the statistical energy model, sound reflection and sound diffraction processing were investigated.
出处 《铁道学报》 EI CAS CSCD 北大核心 2013年第1期101-107,共7页 Journal of the China Railway Society
基金 国家高技术研究发展计划(863计划)(2011AA11A103) 国家自然科学基金(51008250) 教育部新世纪优秀人才支持计划(NCET-10-0701) 高等学校博士学科点专项基金(20110184110020) 四川省青年科技基金(2010JQ0018) 四川省科技计划(2010JY0026) 西南交通大学扬华之星项目
关键词 高速铁路 桥梁 振动 噪声 预测 high-speed railway bridge vibration noise prediction
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参考文献11

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