A denoising method for blasting vibration signals based on improved EMD

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Journal of Vibration and Shock ›› 2025, Vol. 44 ›› Issue (1) : 212-220.

SHOCK AND EXPLOSION

A denoising method for blasting vibration signals based on improved EMD

YAN Peng1, ZHANG Yunpeng*1,2, ZHOU Qianqian3, YANG Xi1

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Abstract

Aiming at the problems of end effect and poor signal noise reduction effect in empirical mode decomposition (EMD), according to the idea of extension-decomposition-clustering-noise reduction-reconstruction, a blasting vibration signal noise reduction method based on improved EMD is proposed. The method combined the characteristics of the comprehensive similarity index while taking into account the shape and amplitude similarity of the extension signal. , the clustering property of K-means algorithm and the noise reduction advantage of wavelet packet. It could not only eliminate the end effect of EMD, but also had a good noise reduction effect. The results show that compared with polynomial fitting and boundary local characteristic extension methods, the improved EMD method has the lowest energy error and mean square error (MSE) in simulation signal end effect suppression test. In the noise reduction of the measured blasting vibration signal, the improved EMD method has the highest signal to noise ratio (20.94 dB) and the lowest root mean square error (0.0031) compared with EMD and variational modal decomposition (VMD) methods. The improved EMD has the best performance in preserving low and medium frequency vibration signals at 0−200 Hz, the best filtering effect on high frequency noise above 200 Hz.

Key words

blasting vibration signal / empirical mode decomposition（EMD） / end effect / K-means algorithm / wavelet packet / noise reduction

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YAN Peng1, ZHANG Yunpeng1, 2, ZHOU Qianqian3, YANG Xi1. A denoising method for blasting vibration signals based on improved EMD[J]. Journal of Vibration and Shock, 2025, 44(1): 212-220

References

[1] 谢全民, 龙源, 钟明寿, 等. SGWT在爆破振动信号信噪分离中的应用研究 [J]. 振动与冲击, 2012, 31(01): 24-28+43.
XIE Q M, LONG Y, ZHONG M T, et al. Application of SGWT in separation of noises from a blast vibration signal [J]. Journal of Vibration and Shock, 2012, 31(1): 24-28.
[2] ZHAI M Y. Seismic data denoising based on the fractional Fourier transformation [J]. Journal of Applied Geophysics, 2014, 109: 62-70.
[3] 王海龙, 赵岩, 王海军, 等. 基于CEEMDAN-小波包分析的隧道爆破信号去噪方法[J]. 爆炸与冲击, 2021, 41(05): 125-137.
WANG H L, ZHAO Y, WANG H J, et al. De-noising method of tunnel blasting signal based on CEEMDAN decomposition-wavelet packet analysis [J]. Explosion and Shock Waves, 2020, 40(8): 1-15.
[4] 马宏伟, 张大伟, 曹现刚, 等. 基于EMD的振动信号去噪方法研究 [J]. 振动与冲击, 2016, 35(22): 38-40.
MA H W, ZHANG D W, CAO X G, et al. Vibration signal de-noising method based on empirical mode decomposition [J]. Journal of Vibration and Shock, 2016, 35(22): 38-40.
[5] 彭亚雄, 刘广进, 苏莹, 等. 基于变分模态分解算法的隧道爆破振动信号光滑降噪模型 [J]. 振动与冲击, 2021, 40(24): 173-179
PENG Y X, LIU G J, SU Y, et al. A smooth denoising model of tunnel blasting vibration signal based on VMD [J]. Journal of Vibration and Shock, 2021, 40(24): 173-179.
[6] 梁黎明, 王茂芝, 徐文皙, 等. 综合斜率和三次样条的EMD端点效应抑制方法 [J]. 振动与冲击, 2022, 41(14): 70-76.
LIANAG L M, WANG M Z, XU W X, et al. Restriction of the end effect of EMD by utilizing slope and cubic spline based methods [J]. Journal of Vibration and Shock, 2022, 41(14): 70-76.
[7] 杨剑锋, 石戈戈, 周天奇, 等. 基于自适应序贯相似性检测波形匹配延拓的EMD端点效应抑制 [J]. 振动与冲击, 2018, 37(18): 121-125.
YANG J F, SHI G G, ZHOU T Q, et al. Waveform extension method based on similarity sequential detection for the end effects reduction of EMD [J]. Journal of Vibration and Shock, 2018, 37(18): 121-125.
[8] 李奇, 刘自然, 颜丙生, 等. 基于Cubic Hermite的改进EMD算法 [J]. 机床与液压, 2021, 49(21): 186-190.
LIU Q, LIU Z R, YAN B S, et al. Improved EMD algorithm based on Cubic Hermite [J]. Machine Tool & Hydraulics, 2021, 49(21): 186-190.
[9] 方赛银, 邱荣祖, 李明. 基于改进EMD算法的木材声发射信号特征研究 [J]. 振动与冲击, 2018, 37(23): 292-298.
FANG S Y, QIU R Z, LI M. Wood AE signal features based on improved EMD algorithm [J]. Journal of Vibration and Shock, 2018, 37(23): 292-298.
[10] 刘霖雯, 刘超, 江成顺. EMD新算法及其应用 [J]. 系统仿真学报, 2007, 19(02): 446-447+464.
LIU L W, LIU C, JIANG C S. Novel EMD algorithm and its application [J]. Journal of System Simulation, 2007, 19(02): 446-447+464.
[11] 宿文才, 张树团, 刘陵顺. 基于改进极值波延拓的极点对称模态分解端点效应抑制方法 [J]. 电工技术学报, 2020, 35(S1): 294-301.
SU W C, ZHANG S T, LIU L S. Extreme-point symmetric mode decomposition endpoint reduction method based on improved extremal wave extension [J]. Transactions of China Electrotechnical Society, 2020, 35(S1): 294-301.
[12] 孟宗,顾海燕,李姗姗. 基于神经网络集成的B样条经验模态分解端点效应抑制方法 [J]. 机械工程学报, 2013, 49(09): 106-112.
MENG Z, GU H Y, LI S S. Restraining method for end effect of B-spline empirical mode decomposition based on neural network ensemble [J]. Journal of Mechanical Engineering, 2013, 49(09): 106-112.
[13] 荣钦彪. 改进端点效应和抑制模态混叠的EMD方法研究[D]. 天津: 天津大学, 2018: 19-22.
[14] 王婷. EMD算法研究及其在信号去噪中的应用[D]. 哈尔滨: 哈尔滨工程大学, 2010: 30-38.
[15] 高强, 段晨东, 赵艳青, 等. 基于最大相关波形延拓的经验模式分解端点效应抑制方法[J]. 振动与冲击, 2013, 32(02): 62-66.
GAO Q, DUAN C D, ZHAO Y Q, et al. A maximal correlation waveform extension method for end effects reduction of empirical mode decomposition [J]. Journal of Vibration and Shock, 2013, 32(02): 62-66.
[16] 晏飞, 杨涛, 庞毅飞, 等. 基于波形平均的经验模态分解端点效应抑制方法 [J]. 机械设计与制造, 2017, (05): 212-215.
YAN F, YANG T, PANG Y F, et al. End effect reduction of empirical mode decomposition based on waveform averaging [J]. Machinery Design & Manufacture, 2017, (05): 212-215.
[17] 李文华, 姜惠, 赵正元, 等. 基于波形匹配端点延拓法优化的经验模态分解算法在铁路继电器参数降噪上的应用 [J]. 电工技术学报, 2022, 37(10): 2656-2664.
LI W H, JIANG H, ZHAO Z Y, et al. Application of empirical mode decomposition algorithm based on waveform matching endpoint continuation method in noise reduction of railway relay parameters [J]. Transactions of China Electrotechnical Society, 2022, 37(10): 2656-2664.
[18] 胡勇, 郑黎明, 贾科, 等. 基于Tanimoto相似度的光伏场站送出线路纵联保护 [J]. 电力系统保护与控制, 2021, 49(03): 74-79.
HU Y, ZHENG L M, JIA K, et al. Pilot protection based on Tanimoto similarity for a photovoltaic station transmission line [J]. Power System Protection and Control, 2021, 49(03): 74-79.
[19] 陶维青, 李雪婷, 华玉婷, 等. 基于曼哈顿平均距离和余弦相似度的配网单相接地故障定位 [J]. 电力工程技术, 2023, 42(02): 130-138.
TAO W Q, LI X T, HUA Y T, et al. Fault location of single-phase grounding fault based on Manhattan average distance and cosine similarity in distribution network [J]. Electric Power Engineering Technology, 2023, 42(02): 130-138.
[20] 王惠琴, 侯文斌, 彭清斌, 等. 基于K均值聚类的SPPM分步分类检测算法[J]. 通信学报, 2022, 43(01): 161-171.
WANG H Q, HOU W B, PENG Q B, et al. Step-by-step classification detection algorithm of SPPM based on K-means clustering [J]. Journal on Communications, 2022, 43(01): 161-171.
[21] 王学敏, 黄方林. EMD端点效应抑制的一种实用方法 [J]. 振动. 测试与诊断, 2012, 32(03): 493-497+520.
WANG X M, HUANG F L. Practical method to restrain the end effect of EMD [J]. Journal of Vibration,Measurement & Diagnosis, 2012, 32(03): 493-497+520.
[22] 杨君保. 基于改进K-means算法的大跨屋盖结构表面风荷载分区研究[D]. 石家庄: 石家庄铁道大学, 2023: 11-12.
[23] HUANG D, CUI S, LI X X. Wavelet packet analysis of blasting vibration signal of mountain tunnel [J]. Soil Dynamics and Earthquake Engineering, 2019, 117(117): 72-80.
[24] 易文华, 刘连生, 闫雷, 等. 基于EMD改进算法的爆破振动信号去噪[J]. 爆炸与冲击, 2020, 40(09): 77-87.
YI W H, LIU L S, YAN L, et al. Study on vibration signal de-noising based on EMD improved algorithm [J]. Explosion and Shock Waves, 2020, 40( 9): 75-85.
[25] YI W H, YAN L, WANG Z H, et al. Geotechnical engineering blasting: a new modal aliasing cancellation methodology of vibration signal de-noising [J]. Earthquake Engineering and Engineering Vibration, 2022, 21(02): 313-323.