摘要:铁路是我国交通运输中重要组成部分，其对于我国的经济发展和人口流动都起着至关重要的作用。在这之中轨道电路是保障列车能够安全稳定运行的重要组成部分，因此我们必须经常对其进行检查以确保它的稳定性。而在移频轨道电路信号的检测及控制系统中，往往会因为受到环境的影响而混入一些干扰的噪声信号，它们会使测量结果产生很大的误差。这些误差将导致后勤工作无法进行，甚至会引起列控程序的紊乱，从而造成控制系统中执行机构产生误动作。在受干扰背景下有效地监测信号，不仅与信号的形式和干扰的性质有关，也与信号的检测与处理的方式有关。

    与此同时，本文用小波变换和小波包分析方法对以上两种信号进行了进一步的研究，波变换就是应传统的傅立叶变换不能够满足信号处理的要求而产生的，它是一种信号的时间---尺度（时间---频率）分析方法，具有多分辨率分析的特点，而且在时频两域都具有表征信号局部特性的能力，是一种窗口大小固定不变但其形状可改变，时间窗和频率窗都可以改变的时频局部化分析方法。而小波包较小波变换是一种更加精细的分解方法，能将高频部分进一步划分，从而能使高频部分的频域分辨率进一步提高。因此基于小波变换的数字通信信号处理能有效解决在数字通信信号处理在使用傅立叶变换进行滤波消噪、突变信号检测、非平稳信号视频分析、系好特征提取等所遇到的问题。同时本文还给出了Matlab的仿真结果针对交流计数信号的检测，提出了去噪。从仿真结果可以看出，小波分析检测交流计数信号的误差小，抗干扰能力强，利用该方法有效的克服了传统方法0、1阈值很难选取的缺点，并能得到上下边频利用小波分析检测这两种信号的方法对提高铁路信号检测的准确度具有重要的现实意义和实用价值。77920

毕业论文关键字：小波变换；小波包分析 ；交流计数信号；移频2FSK信号

Track circuit frequency shift signal detection and denoising

Abstract：Railway is an important part of China's transportation, which plays a vital role in China's economic development and population movement。 In this way, the track circuit is an important part of the safe and stable operation of the train, so we must always check it to ensure its stability。The frequency shift of the track circuit signal detection and control systems, often because of the environmental impact of mixing some of the interference noise signal, they will make measurements to produce large errors。 These errors will result in logistical work can not proceed, even cause the column to control the program of the disorder, resulting in malfunction of control systems in implementing agencies。 Effective monitoring in the context of interference signals, not only in the form of the signal and the nature of the interference signal detection and processing。

At the same time, the above two signals, the wavelet transform and wavelet packet analysis method for the further study of wave transformation should the traditional Fourier transform is not able to meet the requirements of signal processing to produce, it is a signal of the time --- scale (time --- frequency) analysis method, the characteristics of multi-resolution analysis and frequency domain characterization of the local characteristics of the signal in time, a window size is fixed but can change its shape time window and frequency window can be changed when the frequency localization。 Wavelet packet transform small wave is a more sophisticated decomposition method, high frequency components can be further pided, in order to make the high-frequency part of the frequency domain resolution to further improve。 Therefore, the digital communication signal processing based on wavelet transform can effectively solve the filtering de-noising using a Fourier transform in the digital communication signal processing, mutations in the signal detection, video analysis of non-stationary signals, Department of the feature extraction, such as the problems encountered。 The article also gives the Matlab simulation results for the exchange of counting signal detection, proposed denoising。 From the simulation results can be seen that the wavelet analysis of signal detection AC counting error is small, strong anti-jamming capability, using the method to overcome the shortcomings of traditional methods 0,1 threshold is difficult to select, and get below the frequency of using wavelet the analysis has important practical significance and practical value of these two signal detection methods to improve the accuracy of the railway signal detection。