基于EEMD的应答器上行链路信号处理的研究
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摘要
应答器是列控系统中重要的点式车-地信息传输设备,地面应答器与列控车载设备之间的信息传输对列车的安全运行有重要影响。EMD是对信号进行平稳化处理的过程,根据信号频率特征自适应的分解为本征项和趋势项, EEMD是在EMD的基础上进行的改进,能够有效抑制EMD的模式混淆现象。通过对BUS信号特点以及应答器系统工作原理进行详细分析的基础上,利用EEMD算法将BUS信号分解为不同的IMF分量;对其进行FFT变换得到不同的频谱图;最后重构BU-2FSK调频信号分量,达到消除噪声干扰的目的。仿真结果表明:采取EEMD可以有效地检测并提取BU-2FSK调频信号,是一种有效的信号处理方式。
Balise is an important point type vehicle to ground information transmission equipment in the train control system. The information transmission between the ground balise and the on-board train control equipment has an important influence on the safe operation of the train. EMD is a process of smoothing the signal, which is adaptively decomposed into eigenvalues and trend terms according to the frequency characteristics of the signal. However, there are some problems in the practical application of EMD called pattern confusion. EEMD is an improvement based on EMD, which can effectively restrain EMD's pattern confusion. On the basis of the detailed analysis of the characteristics of the BUS signal and the operating principle of the balise system, the BUS FM signals were decomposed into different IMF components with the means of EEMD algorithm, and different spectrum was obtained by FFT transformation. Finally, the IMF of BU-2 FSK FM signal was reconstructed for the purpose of noise elimination. The simulation results show that the EEMD can detect and extract BU-2 FSK FM signal, which is an effective signal disposing method.
Balise is an important point type vehicle to ground information transmission equipment in the train control system. The information transmission between the ground balise and the on-board train control equipment has an important influence on the safe operation of the train. EMD is a process of smoothing the signal, which is adaptively decomposed into eigenvalues and trend terms according to the frequency characteristics of the signal. However, there are some problems in the practical application of EMD called pattern confusion. EEMD is an improvement based on EMD, which can effectively restrain EMD's pattern confusion. On the basis of the detailed analysis of the characteristics of the BUS signal and the operating principle of the balise system, the BUS FM signals were decomposed into different IMF components with the means of EEMD algorithm, and different spectrum was obtained by FFT transformation. Finally, the IMF of BU-2 FSK FM signal was reconstructed for the purpose of noise elimination. The simulation results show that the EEMD can detect and extract BU-2 FSK FM signal, which is an effective signal disposing method.
引文
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[9] 任斌斌,谭海燕,马成群,等.基于白噪声分离的集合经验模态分解心电信号去噪方法研究[J].生物医学工程学杂志,2016,32(2):221-226.REN Binbin, TAN Haiyan, MA Chengqun, et al. Research on Demagnetration Method of ECG Signal Based on Aggregate Empirical Mode Decomposition Based on White Noise Separation[J]. Journal of Biomedical Engineering,2016,33(2):221-226.
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[12] 盖广洪.经验模态分解的一种改进算法[J].西安交通大学学报,2004,38(11):1199-1202.GAI Guanghong. An Improved Algorithm for Empirical Mode Decomposition[J]. Journal of Xi'an Jiaotong University,2004,38(11):1199-1202.
[13] 秦娜,金炜东,黄进,等.基于EEMD样本熵的高速列车转向架故障特征提取[J].西南交通大学学报,2014,49(1):27-32.QIN Na, JINWeidong, HUANG Jin, et al. Fault Feature Extraction of High-speed Train Bogie Based on EEMD Sample Entropy[J]. Journal of Southwest Jiaotong University, 2014,49 (1): 27-32.
[14] 吕城锦.基于认知控制的应答器上行链路信号处理方法[D].北京:北京交通大学,2016.
[2] 陈满堂,杜普选.采用相位推算法测量低频FSK信号频率[J].北京交通大学学报,2004,28(3):106-109.CHEN Mantang, DU Puxuan. The Low Frequency FSK Signal is Measured by the Phase Estimation Method[J]. Journal of Beijing Jiaotong University,2004,28(3):106-109.
[3] 孙艳朋,贾利民,范明.小波包方法在车载FSK信号中的应用[J].铁道学报,2001,23(2):32-37.SUN Yanpeng, JIA Limin, FAN Ming. Application of Wavelet Packet Method in Vehicle FSK Signal[J]. Journal of China Railway Society,2001,23(2):32-37.
[4] 董昱.区间信号与列车运行控制系统[M].北京:中国铁道出版社,2008:262-275.
[5] 刘霞,黄阳,黄敬,等.基于经验模态分解(EMD)的小波熵阈值地震信号去噪[J].吉林大学学报(地球科学版),2016,46(1):262-269.LIU Xia, HUANG Yang, HUANG Jing, et al. Wavelet Entropy Threshold Seismic Signal Denoising Based on Empirical Mode Decomposition (EMD)[J]. Journal of Jilin University (Earth Science Edition), 2016,46(1): 262-269.
[6] 柳艳红,马瑞军,魏学业.EMD算法在移频信号解调中的应用研究[J].电子测量与仪器学报,2006,20(5):34-38.LIU Yanhong, MA Ruijun, WEI Xueye. Application of EMD Algorithm in Frequency Shift Signal Demodulation[J]. Journal of Electronic Measurement & Instrumentation,2006,20(5):34-38.
[7] 李晶皎,安冬,王骄.基于EEMD和ICA的语音去噪方法[J].东北大学学报(自然科学版),2011,32(11):1554-1557.LI Jingjiao, AN Dong, WANG Jiao. Speech Denoising Method Based on EEMD and ICA[J]. Journal of Northeastern University(Natural Science), 2011,32(11):1554-1557.
[8] 刘佳,杨士莪,朴胜春.基于EEMD的地声信号单通道盲源分离算法[J].哈尔滨工程大学学报,2011,32(2):194-199.LIU Jia, YANG Shie, PU Shengchun. Single-channel Blind Source Separation Algorithm Based on EEMD[J]. Journal of Harbin Engineering University,2011,32(2):194-199.
[9] 任斌斌,谭海燕,马成群,等.基于白噪声分离的集合经验模态分解心电信号去噪方法研究[J].生物医学工程学杂志,2016,32(2):221-226.REN Binbin, TAN Haiyan, MA Chengqun, et al. Research on Demagnetration Method of ECG Signal Based on Aggregate Empirical Mode Decomposition Based on White Noise Separation[J]. Journal of Biomedical Engineering,2016,33(2):221-226.
[10] WU Z H, HUANG N E. Ensemble Empirical Mode Decomposition: a Noise Assisted Data Analysis Method[J]. Advances in Adaptive Data Analysis, 2009, 1(1):1-41.
[11] 曲从善,路廷镇,谭营.一种改进型经验模态分解及其在信号消噪中的应用[J].自动化学报,2010,36(1):67-73.QU Congshan, LU Tingzhen, TAN Ying. An Improved Empirical Mode Decomposition and Application in Signal De-noising[J]. Acta Automatica Sinica,2010,36(1):67-73.
[12] 盖广洪.经验模态分解的一种改进算法[J].西安交通大学学报,2004,38(11):1199-1202.GAI Guanghong. An Improved Algorithm for Empirical Mode Decomposition[J]. Journal of Xi'an Jiaotong University,2004,38(11):1199-1202.
[13] 秦娜,金炜东,黄进,等.基于EEMD样本熵的高速列车转向架故障特征提取[J].西南交通大学学报,2014,49(1):27-32.QIN Na, JINWeidong, HUANG Jin, et al. Fault Feature Extraction of High-speed Train Bogie Based on EEMD Sample Entropy[J]. Journal of Southwest Jiaotong University, 2014,49 (1): 27-32.
[14] 吕城锦.基于认知控制的应答器上行链路信号处理方法[D].北京:北京交通大学,2016.