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Research on Track Frequency Shift Signal Detection Based on Local Mean Decomposition

机译:基于局部均值分解的轨道频移信号检测研究

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The track frequency shift signal reflects the status of signal light in front of the train. Due to the development of high-speed railways, the main demodulation method, improved Fast Fourier Transform (FFT) is unable to meet requirement of limited sample time. In this paper, a new signal demodulation method, Local Mean Decomposition(LMD) is introduced to detect frequencies of the signal. LMD adaptively decompose complicated signal into a set of single-component signals, each of which has physical meaning. In order to solve end effect of LMD, an adaptive waveform matching extending method is proposed. In addition, a noise-assisted analysis method is recommended to reduce the noise effect. The simulation results show that compared with the improved FFT, LMD has better performance on detecting track frequency shift signal. LMD nearly has no requirement on signal sampling time but has twice the accuracy of FFT with 5s sampling time.
机译:轨道频移信号反映了火车前面的信号灯的状态。由于高速铁路的开发,主要解调方法,改进的快速傅里叶变换(FFT)无法满足有限的采样时间的要求。在本文中,引入了一种新的信号解调方法,局部平均分解(LMD)以检测信号的频率。 LMD将复杂的信号自适应地分解为一组单组分信号,每个信号具有物理含义。为了解决LMD的结束效果,提出了一种自适应波形匹配的延伸方法。此外,建议噪声辅助分析方法降低噪声效果。仿真结果表明,与改进的FFT相比,LMD在检测轨道频移信号上具有更好的性能。 LMD几乎没有关于信号采样时间的要求,但具有5S采样时间的FFT的准确性。

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