项目名称: 高速列车表面脉动压力测试原理与信号提取方法研究
项目编号: No.51475387
项目类型: 面上项目
立项/批准年度: 2015
项目学科: 机械、仪表工业
项目作者: 陈春俊
作者单位: 西南交通大学
项目金额: 84万元
中文摘要: 高速列车表面的脉动压力是列车行驶时,列车周围附近的空气湍流场形成的表面气压脉动。脉动压力引发气动噪声与结构振动等问题。为了对气动噪声和振动的预测与控制,需要知道列车表面脉动压力信号或功率谱。但受计算机硬件及湍流模型假设所限制,列车表面脉动压力的数值模拟结果需要试验值来验证。列车表面脉动压力幅值低、频带宽,测试要求对流场影响小,测试环境存在多因素耦合干扰,造成测试困难和测试信号的信噪比低,难于有效提取脉动压力。目前列车表面压力只能通过测试信号滤波提取出平均压力,而脉动压力尚不能有效提取。课题拟采用理论分析、数值模拟、模型试验相结合方法,对传感器测试原理进行内部有限元分析,建立内部多因素耦合模型;将希尔伯特-黄变换的经验模态分解法与传感器内部多因素耦合模型结合,用多变量控制与系统辨识理论对脉动压力提取方法展开研究。在应用上,对线路试验信号提取脉动压力及功率谱分析,提出进一步减小脉动压力的措施。
中文关键词: 高速列车;列车空气动力学;脉动压力;压阻式压力传感器;希尔伯特-黄变换
英文摘要: The surface fluctuation pressure on high speed train is formed by turbulent flow field which is around the train when it travels. The fluctuation pressure can cause aerodynamic noise and structural vibration. In order to forecast and control the noise and vibration, the fluctuation pressure signal and power spectrum are needed. But it's always limited by Computer hardware conditions and Turbulence model assumptions, the fluctuation pressure's numerical modeling result need test to prove. The fluctuation pressure's amplitude is low, the band is wide, and the test require little influence to flow field. However there are lots of interference factors in the testing environment, so the test is difficult and the test signal's SNR is low. Now, the surface pressure can only be extracted by the signal's LPF, which is average pressure, but the fluctuation pressure can't be extracted effectively. This project will combine theoretical analysis, numerical simulation, and model test, build internal multi-factors coupling model of sensor's test principium and interior finite element modeling. Adopt the empirical mode decomposition of Hilbert-Huang transform, combining with multi-factors coupling model of sensors, and multivariable control as well as system identification theory. On the application, extract the fluctuation pressure from the test signal and analyze its power spectrum, put forward measures to decrease the fluctuation.
英文关键词: High-speed train;Train aerodynamics;Fluctuation pressure;Piezoresistive pressure sensor;Hilbert-Huang transform