【摘要】 针对非平稳信号时-频分析中单独使用Cohen核计算二次分布时出现交叉项的实际情况,提出了一种基于EMD和Cohen核的时-频分析方法。首先将信号进行经验模态分解(EMD),然后将分解后的多个固有模态函数(IMF)分别进行Cohen核分布的时-频变换。将仿真信号与理想的仿真结果进行比较,证明此方法能够有效的抑制二次分布中的交叉项。将此方法应用到基于轴箱加速度信号的轨道不平顺分析中,得到的结论与利用轨检车得到的轨道不平顺信息一致,并明显优于常规应用于列车走行部信号分析的频谱分析以及包络线分析方法。此方法对于弥补轨检车的各种不足,高速高密度的进行轨道不平顺的在线监测具有重要应用价值。更多还原

【Abstract】 To minimize cross-term interferences,a method based on empirical mode decomposition(EMD) and Cohen’s kernel was presented.With the method,firstly,the time-domain signal was separated into multiple intrinsic mode functions(IMFs) using EMD,then Cohen’s kernel distributions of the IMFs were calculated.And a sum of all Cohen’s kernel distributions was acquired.This approach was testified with three typical simulation signals and the results agreed well with the theoretical ones.At last,this approach was applied to analyze the track irregularity based on the axle-box acceleration.Compared with the results using a track inspection car,the consistent results were obtained.It was indicated that this approach is good to compensate some shortage of track inspection vehicle,and it plays an important role in high-speed high-density on-line mornitoring of track irregularity.更多还原