首页|基于改进HHT算法的重载铁路信号自动化解调方法设计

基于改进HHT算法的重载铁路信号自动化解调方法设计

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重载列车在铁路运行过程中,信号容易受到干扰和失真,影响列车的安全性.该文提出一种基于改进HHT算法的重载铁路信号自动化解调方法.采用小波阈值去噪方法改进HHT算法中的集成经验模态分解成多个IMF分量后,利用小波阈值去噪法对含有噪声的分量展开去噪.使用Bedrosian乘积定理获取全新的递归函数,改进HHT算法中的希尔伯特变换,将纯调频信号作为新的重载环境面的铁路信号,基于递归Hilbert变换实现重载铁路信号自动化解调.实验测试结果表明,所提方法解调后的信号频率与仿真信号频率基本吻合,频带利用率最高可达9.3%,具有良好的信号解调能力.
Design of Automatic Demodulation Method for Heavy Haul Railway Signal Based on Improved HHT Algorithm
During the operation of heavy-loaded trains on railways,signals are prone to interference and distortion,which affects the safety of the train.Propose an automated demodulation method for heavy-duty railway signals based on an improved HHT algorithm.Using the wavelet threshold denoising method to improve the integrated empirical mode decomposition in the HHT algorithm into multiple IMF components,the wavelet threshold denoising method is used to denoise the noisy components.Using the Bedrosian product theorem to obtain a new recursive function,im-proving the Hilbert transform in the HHT algorithm,using pure frequency modulation signals as new railway signals in heavy load environments,and implementing automatic demodulation of heavy load railway signals based on recur-sive Hilbert transform.The experimental test results show that the demodulated signal frequency of the proposed method is basically consistent with the simulated signal frequency,with a maximum frequency band utilization rate of 9.3%,and has good signal demodulation ability.

improved HHT algorithmheavy haul railway signalautomated demodulationwavelet thresholdensemble empirical mode decomposition

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国能朔黄铁路发展有限责任公司,原平 034100

改进HHT算法 重载铁路信号 自动化解调 小波阈值 集合经验模态分解

朔黄铁路公司科技创新项目

SHYP-22-09

2024

自动化与仪表
天津市工业自动化仪表研究所 天津市自动化学会

自动化与仪表

CSTPCD
影响因子:0.548
ISSN:1001-9944
年,卷(期):2024.39(1)
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