| 基于集合经验模态分解-小波阈值方法的爆破振动信号降噪方法 |
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| 引用本文： | 费鸿禄,刘梦,曲广建,高英. 基于集合经验模态分解-小波阈值方法的爆破振动信号降噪方法[J]. 爆炸与冲击, 2018, 38(1): 112-118. DOI: 10.11883/bzycj-2016-0148 |
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| 作者姓名： | 费鸿禄 刘梦 曲广建 高英 |
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| 作者单位： | 辽宁工程技术大学爆破技术研究院,辽宁阜新,123000;广州中爆数字信息科技股份有限公司,广东广州,510670;华南理工大学计算机科学与工程学院,广东广州,510641 |
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| 摘 要： | 为了更好地消除混杂在爆破信号中的噪声，引入一种基于集合经验模态分解和小波阈值共同作用的降噪方法。首先将信号进行集合经验模态分解，然后选择含噪的模态函数分量进行小波阈值降噪处理，最后把处理后的分量和未处理的分量进行叠加，重构的信号即为降噪信号。该方法不仅能有效的去除噪声，还能使爆破波形保留其真实性和完整性。
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| 关 键 词： | 爆破信号 集合经验模态分解 小波阈值 降噪 |
| 收稿时间： | 2016-05-25 |
A method for blasting vibration signal denoising based on ensemble empirical mode decomposition-wavelet threshold |
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| FEI Honglu,LIU Meng,QU Guangjian,GAO Ying. A method for blasting vibration signal denoising based on ensemble empirical mode decomposition-wavelet threshold[J]. Explosion and Shock Waves, 2018, 38(1): 112-118. DOI: 10.11883/bzycj-2016-0148 |
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| Authors: | FEI Honglu LIU Meng QU Guangjian GAO Ying |
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| Affiliation: | 1.Institute of Blasting Technique, Liaoning Technical University, Fuxin 123000, Liaoning, China2.Guangzhou China Blast Digital Information Technology Co., Ltd., Guangzhou 510670, Guangdong, China3.School of Computer Science & Engineering, South China University of Technology, Guangzhou 510641, Guangdong, China |
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| Abstract: | In this work we proposed a method based on ensemble empirical mode decomposition (EEMD) and wavelet threshold for eliminating the noise contained a in blasting signal.Following this method,the signal is firstly decomposed using the ensemble empirical mode decomposition;then,the intrinsic mode function with noise is processed by the wavelet threshold denoising;and,finally,the processed signal is superimposed on the untreated component of the signal,and the signal thus reconstructed is the denoised signal.This method can not only can effectively remove the noise,but also enable the burst wave form to retain its authenticity and integrity |
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