首页|基于WPD-EMD-WPD的地下工程微震信号降噪方法研究

基于WPD-EMD-WPD的地下工程微震信号降噪方法研究

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微震信号中的背景噪声会影响初至拾取、震源定位及参数反演,合理有效的降噪方法是微震监测技术成功应用于工程建设的重要基础.本文提出一种基于WPD-EMD-WPD的方法抑制噪声,并采用信偏比衡量降噪效果.该方法首先对含噪信号小波包预降噪,实现初次滤波;然后对预降噪后的信号进行经验模态分解(Empirical Mode Decomposition,EMD),自适应分解得到IMFS,通过相关系数法确定IMFS分解分量位置;最后,对分界分量之前的高频分量小波包降噪,再与低频分量重构.分别使用小波包、EMD、EMD-WPD、WPD-EMD-WPD 4种方法进行仿真实验,对含噪Ricker子波降噪处理,通过对比降噪前后的降噪效果衡量指标、频谱图、波形图对比发现,WPD-EMD-WPD降噪效果更优,且信偏比与其他降噪指标有良好对应性.将该方法应用于国内某大型水电工程地下洞室,结果表明,该方法能获得更低的信偏比,且能更好地反映初至时刻和岩石微破裂信息.
RESEARCH ON DENOISING METHOD FOR MICROSEISMIC SIGNALS OF UNDERGROUND ENGINEERING BASED ON WPD-EMD-WPD
The background noises in microseismic signals have great influences on the first arrival picking,source location,and parameter inversion.Reasonable and effective noise reduction methods are a significant basis for the reliable application of microseismic monitoring technology in engineering construction.In this paper,a noise sup-pression method based on WPD-EMD-WPD is proposed,and the signal deviation ratio is used to measure the noise reduction effect.In this method,the signal containing noise is denoised by wavelet packet in advance to achieve the first filtering.Then the Empirical Mode Decomposition(EMD)adaptive decomposition is performed on the denoised signal to obtain IMFS.The position of the EMD decomposition component is determined by the correlation coeffi-cient method.Finally,the wavelet packet of the high-frequency component before the boundary component is de-noised and reconstructed with the low-frequency component.Wavelet packets,EMD,EMD-WPD,and WPD-EMD-WPD are used for noise Ricker wavelet noise reduction in simulation experiments.By comparing the measurement index,spectrum diagram,and waveform diagram of noise reduction before and after noise reduction,it is found that the noise reduction effect of the WPD-EMD-WPD method is better,and the signal deviation ratio has good corre-spondence with other noise reduction indices.

Microseismic signal denoisingSignal deviation ratioEmpirical mode decompositionCorrelation co-efficientWavelet packet

林鑫、李彪、杨春鸣、钟维明、徐奴文

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西南石油大学地球科学与技术学院,成都 610500,中国

四川大渡河双江口水电开发有限公司,马尔康 624099,中国

中国电建集团成都勘测设计研究院有限公司,成都 610072,中国

四川大学,水力学与山区河流开发保护国家重点实验室,成都 610065,中国

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微震信号降噪 信偏比 经验模态分解 相关系数 小波包

国家自然科学基金项目国家自然科学基金项目四川省杰出青年基金项目四川省杰出青年基金项目

51809221421771435180922142177143

2024

工程地质学报
中国科学院地质与地球物理研究所

工程地质学报

CSTPCD北大核心
影响因子:1.215
ISSN:1004-9665
年,卷(期):2024.32(2)
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