基于小波变换的高速列车表面脉动压力提取

摘要

It is always the case that micro-piezoresistive pressure sensors are affected by some interference signals during the process of measuring the high-speed trains' surface pressure,which makes signal to noise ratio (SNR)of the fluctuating pressure low. In order to extract the fluctuating pressure effectively,a sensor output model was established. An effective denoising method based on wavelet threshold was proposed,which determines the decomposition level by introducing a correlation coefficient and counts the stratification threshold according to 3σprinciple. This method was then used to denoise static test signals of a certain type of CRH EMUs (electric multiple units)and extract the fluctuating pressure from the surface pressure of the EMUs at 200 km/h,and on this basis to build a power spectrum model of fluctuation pressure. The results show that the proposed method can extract the fluctuating pressure effectively,and the pressure at measuring points fluctuates constantly in the amplitude range of ± 20 Pa and mainly in the frequency range of 0-200 Hz. The established power spectrum model of fluctuating pressure provides a theoretical guidance for the vibration damping and noise reduction of trains.%高速列车表面压力测试过程中，为了克服微型压阻式气压传感器测试的脉动压力信噪比低的缺点，有效提取出脉动压力，建立了传感器输出模型；利用相关系数法确定分解层数，根据3σ原则计算分层阈值，提出一种小波变换阈值去噪方法。用该方法对CRH（China railway high-speed）某型动车组静态测试信号进行去噪处理；并进行200 km／h动车组表面压力测试信号脉动压力的提取，建立了脉动压力功率谱模型。研究结果表明：该方法能有效提取出列车表面脉动压力，测点处脉动压力的幅值在±20 Pa范围内时刻波动，频率主要集中在0～200 Hz；建立的脉动压力功率谱模型为列车减振和降噪提供理论指导。