[1]王海龙①,李帅①,赵岩②,等.CEEMDAN小波包联合降噪的优化方法[J].爆破器材,2021,50(04):48-53.[doi:10.3969/j.issn.1001-8352.2021.04.009]
　WANG Hailong,LI Shuai,ZHAO Yan,et al.Optimization Method of CEEMDAN-Wavelet Packet Joint Noise Reduction[J].EXPLOSIVE MATERIALS,2021,50(04):48-53.[doi:10.3969/j.issn.1001-8352.2021.04.009]
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CEEMDAN小波包联合降噪的优化方法()
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《爆破器材》[ISSN:1001-8352/CN:32-1163/TJ]

卷:
50
期数:
2021年04
页码:
48-53
栏目:
爆破技术
出版日期:
2021-07-07

文章信息/Info

Title:
Optimization Method of CEEMDAN-Wavelet Packet Joint Noise Reduction
文章编号:
5555
作者:
王海龙①; 李帅①; 赵岩②; 王晟华③
①河北建筑工程学院土木工程学院（河北张家口，075000）
②中国矿业大学（北京）力学与建筑工程学院（北京，100083）
③北旺集团有限公司（河北承德，067400）
Author(s):
WANG Hailong①;  LI Shuai①;  ZHAO Yan②;  WANG Shenghua③
① School of Civil Engineering, Hebei University of Architecture (Hebei Zhangjiakou, 075000)
② School of Mechanics and Civil Engineering, China University of Mining and Technology (Beijing) (Beijing,100083)
③ North Prosperous Construction Group Co., Ltd. (Hebei Chengde, 067400)
关键词:
隧道爆破振动信号; CEEMDAN分解; 小波包分析; 多尺度排列熵; SG平滑滤波; 降噪
Keywords:
vibration signal in tunnel blasting;  CEEMDAN decomposition;  wavelet packet analysis;  multi-scale permutation entropy;  SG smoothing filter;  noise reduction
分类号:
TU751.9
DOI:
10.3969/j.issn.1001-8352.2021.04.009
文献标志码:
A
摘要:
针对实测隧道爆破振动信号降噪效果不理想的问题，引入多尺度排列熵的概念，用来筛选含噪明显的本征模态分量，并结合SG（savitzky-golay）平滑滤波方法提出了一种完备的自适应噪声经验模态分解（CEEMDAN）和小波包联合降噪的优化方法，通过信噪比(SNR)、均方根差(RMSE)、相关系数、自相关系数对仿真实验和实测信号处理结果进行对比分析。结果表明，CEEMDAN小波包联合降噪优化方法提高了信号降噪效果，且有效保留了原始信号中的特征信息，可以应用到类似爆破振动信号的降噪处理中。
Abstract:
Aiming at the problem that the noise reduction outcome of vibration signal in tunnel blasting is not ideal, multi-scale permutation entropy was introduced to filter out the eigenmode components with obvious noise. Combined with SG (savitzky-golay) smoothing filtering method, a complete adaptive noise empirical mode decomposition (CEEMDAN) and wavelet packet joint denoising optimization method was proposed. Results of simulation experiments and measured signal processing were compared and analyzed by signal-to-noise ratio (SNR), root mean square error (RMSE), correlation coefficient, and autocorrelation coefficient. It shows that the method improves the noise reduction outcome and effectively retains the characteristic information in the original signal. It can be applied to the noise reduction processing of similar blasting vibration signals.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期：2020-12-18
基金项目：国家自然科学基金（51878242）；河北建筑工程学院校级研究生创新基金（XY202116）
第一作者：王海龙（1965-），男，博士，教授，主要从事隧道工程的安全性评价与超前支护机理研究。E-mail:wanghailong-65@163.com
通信作者：李帅（1995-），男，硕士研究生，主要从事隧道爆破振动研究。E-mail:623322532@qq.com
更新日期/Last Update: 2021-07-08