The on-board diagnosis network is the nervous system of high-speed Maglev trains, connecting all controller sensors, and corresponding devices to realize the information acquisition and control. In order to study the ...The on-board diagnosis network is the nervous system of high-speed Maglev trains, connecting all controller sensors, and corresponding devices to realize the information acquisition and control. In order to study the on-board diagnosis network＇s security and reliability, a simulation model for the on-board diagnosis network of high-speed Maglev trains with the optimal network engineering tool （OPNET） was built to analyze the network＇s performance, such as response error and bit error rate on the network load, throughput, and node-state response. The simulation model was verified with an actual on-board diagnosis network structure. The results show that the model results obtained are in good agreement with actual system performance and can be used to achieve actual communication network optimization and control algorithms.展开更多
高速磁浮列车作为一种新型交通工具,运行时的噪声以气动噪声为主,但目前对其气动噪声的研究极少。为了探明其发声机理和辐射特征,以TR08的1︰8缩尺3车编组模型为研究对象,采用大涡模拟(LES)及Kirchhoff-Ffowcs Williams and Hawkings(K-...高速磁浮列车作为一种新型交通工具,运行时的噪声以气动噪声为主,但目前对其气动噪声的研究极少。为了探明其发声机理和辐射特征,以TR08的1︰8缩尺3车编组模型为研究对象,采用大涡模拟(LES)及Kirchhoff-Ffowcs Williams and Hawkings(K-FWH)方程,获取高速磁浮列车气动激扰特性,精细化仿真研究磁浮列车不同速度级下的气动噪声源频谱和空间分布特征,并基于此构建可穿透积分面,对磁浮列车四极子噪声源贡献开展研究。研究结果表明:在400,500和600 km/h 3个速度级下磁浮列车远场最大辐射气动噪声声压级分别为88.7,94.2和98.1 dBA;列车辐射噪声频谱呈现宽峰特征,宽峰在400~700 Hz区间,且随着磁浮列车运行速度的增加缓慢向高频迁移;列车尾车流线型区域及尾流区是最主要的噪声源区,尾车流线型区域仍然以偶极子噪声为主,尾流区则以四极子噪声为主;尾流区的四极子声源辐射能量贡献显著且随车速增加而增大,600 km/h时声辐射能量贡献平均占比约83%,可见高速磁浮列车运行时四极子噪声的影响不容忽视。展开更多
基金supported by the National Natural Science Foundation of China (No. 51007074)the Program for New Century Excellent Talents in University(NECT-08-0825)+1 种基金the Research and Development Project of the National Railway Ministry (2011J016-B)The basic research universities special fund operations(SWJTU11CX141)
文摘The on-board diagnosis network is the nervous system of high-speed Maglev trains, connecting all controller sensors, and corresponding devices to realize the information acquisition and control. In order to study the on-board diagnosis network＇s security and reliability, a simulation model for the on-board diagnosis network of high-speed Maglev trains with the optimal network engineering tool （OPNET） was built to analyze the network＇s performance, such as response error and bit error rate on the network load, throughput, and node-state response. The simulation model was verified with an actual on-board diagnosis network structure. The results show that the model results obtained are in good agreement with actual system performance and can be used to achieve actual communication network optimization and control algorithms.
文摘高速磁浮列车作为一种新型交通工具,运行时的噪声以气动噪声为主,但目前对其气动噪声的研究极少。为了探明其发声机理和辐射特征,以TR08的1︰8缩尺3车编组模型为研究对象,采用大涡模拟(LES)及Kirchhoff-Ffowcs Williams and Hawkings(K-FWH)方程,获取高速磁浮列车气动激扰特性,精细化仿真研究磁浮列车不同速度级下的气动噪声源频谱和空间分布特征,并基于此构建可穿透积分面,对磁浮列车四极子噪声源贡献开展研究。研究结果表明:在400,500和600 km/h 3个速度级下磁浮列车远场最大辐射气动噪声声压级分别为88.7,94.2和98.1 dBA;列车辐射噪声频谱呈现宽峰特征,宽峰在400~700 Hz区间,且随着磁浮列车运行速度的增加缓慢向高频迁移;列车尾车流线型区域及尾流区是最主要的噪声源区,尾车流线型区域仍然以偶极子噪声为主,尾流区则以四极子噪声为主;尾流区的四极子声源辐射能量贡献显著且随车速增加而增大,600 km/h时声辐射能量贡献平均占比约83%,可见高速磁浮列车运行时四极子噪声的影响不容忽视。
