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基于VMD及能量熵的隧道爆破振动信号降噪方法

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为从监测信号中获得真实的隧道爆破振动信号,引入一种基于变分模态分解(Variational Mode Decom-position,VMD)及能量熵的隧道爆破振动信号降噪方法.首先,在不同K值条件下对监测信号进行变分模态分解,得到一系列本征模态分量(Intrinsic Mode Function,IMF),计算各模态分量与原信号的相关系数,根据相关系数确定最优K值;然后,对原信号进行变分模态分解,得到一系列中心频率由高到低的本征模态分量,计算每个模态分量的能量熵,确认噪声与信号的分界;最后将信号分量进行重构,得到降噪后的隧道爆破信号.将该信号降噪方法应用于实际爆破振动信号处理,结果表明:与经验模态分解(Empirical Mode Decomposition,EMD)降噪法相比,信噪比更高,剩余能量百分比更高,均方差更低,反映出所提降噪方法在隧道爆破振动信号处理中具有一定的适用性.
Noise Reduction Method of Tunnel Blasting Vibration Signal Based on VMD and Energy Entropy
In order to obtain the real tunnel blasting vibration signal from the monitoring signal,a denoising method for tunnel blasting vibration signal based on Variational Mode Decomposition(VMD)and energy entropy is introduced.Firstly,the monitoring signal is decomposed by variational modes under different K values to obtain a series of Intrinsic Mode Functions(IMF),and the correlation coefficient between each intrinsic mode function and the original signal is calculated,and the opti-mal K value is determined based on the correlation coefficients.Secondly,the original signal is decomposed by variational modes to obtain a series of intrinsic mode functions with center frequencies from high to low,and the energy entropy of each in-trinsic mode function is calculated to confirm the boundary between noise and signal.Finally,the signal components are recon-structed and the denoised tunnel blasting signal is obtained.The results show that,compared with Empirical Mode Decomposi-tion(EMD)noise reduction method,the signal-to-noise ratio is higher,the percentage of residual energy is also higher,and the mean square error is lower,which shows that the proposed noise reduction method has certain applicability in tunnel blasting vibration signal processing.

tunnel blasting vibration signalvariational mode decompositionenergy entropydenoising

叶海旺、钟航、周汉红、欧阳枧、龙桂华、雷涛、李立峰、王炯辉、赵明生、余红兵

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武汉理工大学资源与环境工程学院,湖北 武汉 430070

矿物资源加工与环境湖北省重点实验室,湖北 武汉 430070

武汉市公安局治安管理局,湖北 武汉 430077

深圳市市政工程总公司,广东 深圳 518000

五矿勘查开发有限公司,北京 100044

保利新联爆破工程集团有限公司,贵州 贵阳 550002

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隧道爆破振动信号 变分模态分解 能量熵 降噪

2024

金属矿山
中钢集团马鞍山矿山研究院 中国金属学会

金属矿山

CSTPCD北大核心
影响因子:0.935
ISSN:1001-1250
年,卷(期):2024.(11)