De-noising method of tunnel blasting signal based on CEEMDAN decomposition-wavelet packet analysis
-
摘要: 针对隧道爆破施工中采集到的实测振动信号，引入一种基于总体平均经验模态分解方法（CEEMDAN分解）联合小波包分析的降噪方法。首先，通过CEEMDAN分解得到多个本征模态分量，利用相关系数筛选出包含噪声的模态分量，并通过模态分量的频谱图及方差贡献率进行校核。然后，利用小波包阈值降噪方法对含有噪声的模态分量进行处理。最后，将未经处理的模态分量与去噪完成的分量重构得到最终纯净的爆破振动信号。同时，通过小波包能量谱分析验证此降噪方法的可行性。本文引入的方法兼具CEEMDAN分解及小波包分析的优点，与现有方法相比，去噪效果较好，可以应用于类似隧道爆破信号的去噪处理中。Abstract: Aiming at the measured vibration signals collected during tunnel blasting construction, a noise reduction method based on the overall average empirical mode decomposition method (CEEMDAN decomposition) combined with wavelet packet analysis was in troduced. First, a series of multiple intrinsic modal components were obtained by CEEMDAN decomposition, and the modal components containing noise were selected using correlation coefficients, checked by the spectrogram and the variance contribution rate of the modal components. Then, the wavelet packet threshold noise reduction method was used to process the modal components containing noise. Finally, the unprocessed modal components and the de-noised components were reconstructed to obtain the final pure blasting vibration signal. At the same time, the feasibility of this noise reduction method has been verified by wavelet packet energy spectrum analysis. This method combines the advantages of CEEMDAN decomposition and wavelet packet analysis. Compared with existing methods, the de-noising effect is better, and it can be applied to the de-noising processing of similar tunnel blasting signals.
-
图 8 小波包降噪处理前后的C15信号
Figure 8. signal (C15) before and after wavelet packet noise reduction
图 9 CEEMDAN-小波包阈值降噪后的信号
Figure 9. CEEMDAN-wavelet packet threshold signal after noise reduction
图 10 用于对比的几种方法的降噪效果
Figure 10. Noise reduction effect of several methods for comparison
图 11 小波包能量占有百分比
Figure 11. Signal energy distribution before and after noise reduction
表 1 本征模态分量（IMF）的相关系数
Table 1. Correlation coefficients of modal components (IMF)
模态分量 C1 C2 C3 C4 C5 C6 C7 C8 C9 C10 C11 C12 C13 C14 ri 0.129 0.103 0.097 0.063 0.051 0.687 0.760 0.562 0.260 0.139 0.023 0.003 0.007 0.001 
下载: 导出CSV
表 2 模态分量（IMF）的方差贡献率
Table 2. Variance contribution rate of modal component (IMF)
方差贡献率 C1 C2 C3 C4 C5 C6 C7 C8 C9 C10 C11 C12 C13 C14 e(j) 1.65 0.07 0.41 0.29 0.23 13.42 38.31 34.98 8.71 1.59 0.28 0.24 0.04 0.01
下载: 导出CSV
表 3 去噪效果对比
Table 3. Comparison of noise reduction effects
去噪方法 η σ 小波包阈值去噪 66.412 1.40×10−4 EMD-小波包联合去噪 84.9511 2.55×10−5 EEMD-小波包联合去噪 84.0313 2.43×10−5 新方法去噪 94.0802 2.40×10−5
下载: 导出CSV
-
[1] 张乐文, 王洪波, 邱道宏, 等. 小波降噪与粒子群优化综合回归爆破震动参数 [J]. 岩土力学, 2014, 35(S2): 338–341. DOI: 10.16285/j.rsm.2014.s2.037.ZHANG L W, WANG H B, QIU D H, et al. Blasting vibration parameters using comprehensive regression of wavelet denoising and particle swarm optimization algorithm [J]. Rock and Soil Mechanics, 2014, 35(S2): 338–341. DOI: 10.16285/j.rsm.2014.s2.037. [2] 王翔, 葛晓霞. 基于小波变换的汽轮机振动信号软阀值消噪技术研究 [J]. 汽轮机技术, 2009, 51(3): 204–206, 228. DOI: 10.3969/j.issn.1001-5884.2009.03.014.WANG X, GE X X. A study on signal thresholding de-noising technique based on the wavelet transform [J]. Turbine Technology, 2009, 51(3): 204–206, 228. DOI: 10.3969/j.issn.1001-5884.2009.03.014. [3] 杨孟, 王瑾, 周西峰, 等. 基于CEEMD和小波包的降噪方法研究 [J]. 南京邮电大学学报(自然科学版), 2018, 38(2): 41–47. DOI: 10.14132/j.cnki.1673-5439.2018.02.007.YANG M, WANG J, ZHOU X F, et al. De-noising method based on CEEMD and wavelet packet [J]. Journal of Nanjing University of Posts and Telecommunications (Natural Science Edition), 2018, 38(2): 41–47. DOI: 10.14132/j.cnki.1673-5439.2018.02.007. [4] CHEN G, LI Q Y, LI D Q, et al. Main frequency band of blast vibration signal based on wavelet packet transform [J]. Applied Mathematical Modelling, 2019, 74: 569–585. DOI: 10.1016/j.apm.2019.05.005. [5] YUAN H P, LIU X L, LIU Y, et al. Analysis of acoustic wave frequency spectrum characters of rock mass under blasting damage based on the HHT method [J]. Advances in Civil Engineering, 2018, 2018: 9207476. DOI: 10.1155/2018/9207476. [6] 邓青林, 赵国彦. 基于EEMD和小波的爆破振动信号去噪 [J]. 爆破, 2015, 32(4): 33–38. DOI: 10.3963/j.issn.1001-487X.2015.04.007.DENG Q L, ZHAO G Y. De-noising of blast vibration signal based on EEMD and wavelet [J]. Blasting, 2015, 32(4): 33–38. DOI: 10.3963/j.issn.1001-487X.2015.04.007. [7] 贾贝, 凌天龙, 侯仕军, 等. 变分模态分解在爆破信号趋势项去除中的应用 [J]. 爆炸与冲击, 2020, 40(4): 045201. DOI: 10.11883/bzycj-2019-0092.JIA B, LING T L, HOU S J, et al. Application of variable mode decomposition in the removal of blasting signal trend items [J]. Explosion and Shock Waves, 2020, 40(4): 045201. DOI: 10.11883/bzycj-2019-0092. [8] 费鸿禄, 刘梦, 曲广建, 等. 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.FEI H L, LIU M, QU G J, et al. 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. [9] 陈仁祥, 汤宝平, 马婧华. 基于EEMD的振动信号自适应降噪方法 [J]. 振动与冲击, 2012, 31(15): 82–86. DOI: 10.13465/j.cnki.jvs.2012.15.015.CHEN R X, TANG B P, MA J H. Adaptive de-noising method based on ensemble empirical mode decomposition for vibration signal [J]. Journal of Vibration and Shock, 2012, 31(15): 82–86. DOI: 10.13465/j.cnki.jvs.2012.15.015. [10] 单仁亮, 白瑶, 宋永威, 等. 冻结立井模型爆破振动信号的小波包分析 [J]. 煤炭学报, 2016, 41(8): 1923–1932. DOI: 10.13225/j.cnki.jccs.2015.1526.SHAN R L, BAI Y, SONG Y W, et al. Wavelet packet analysis of blast vibration signals of freezing shaft model [J]. Journal of China Coal Society, 2016, 41(8): 1923–1932. DOI: 10.13225/j.cnki.jccs.2015.1526. [11] 单仁亮, 宋永威, 白瑶, 等. 基于小波包变换的爆破信号能量衰减特征研究 [J]. 矿业科学学报, 2018, 3(2): 119–128. DOI: 10.19606/j.cnki.jmst.2018.02.003.SHAN R L, SONG Y W, BAI Y, et al. Research on the energy attenuation characteristics of blasting vibration signals based on wavelet packet Transformation [J]. Journal of Mining Science and Technology, 2018, 3(2): 119–128. DOI: 10.19606/j.cnki.jmst.2018.02.003. [12] 邹德臣, 王海亮, 王春慧, 等. 基于HHT分析的浅埋隧道爆破振动控制研究 [J]. 隧道建设, 2014, 34(8): 760–764. DOI: 10.3973/j.issn.1672-741X.2014.08.009.ZHOU D C, WANG H L, WANG C H, et al. Study on blasting vibration control of shallow tunnel based on HHT analysis [J]. Tunnel Construction, 2014, 34(8): 760–764. DOI: 10.3973/j.issn.1672-741X.2014.08.009. [13] 叶红宇, 卓越, 杨小林. 隧道爆破振动信号EEMD分解后小波包降噪法研究 [J]. 铁道建筑, 2018, 58(7): 83–86. DOI: 10.3969/j.issn.1003-1995.2018.07.21.YE H Y, ZHUO Y, YANG X L. Research on wavelet packet denoising of tunnel blasting vibration signals after EEMD decomposition [J]. Railway Engineering, 2018, 58(7): 83–86. DOI: 10.3969/j.issn.1003-1995.2018.07.21. [14] 刘霞, 宋启航. CEEMDAN自适应阈值去噪算法在地震方向的应用 [J]. 重庆大学学报, 2019, 42(7): 95–104. DOI: 10.11835/j.issn.1000-582X.2019.07.011.LIU X, SONG Q H. CEEMDAN adaptive threshold denoising algorithm in application to seismic direction [J]. Journal of Chongqing University, 2019, 42(7): 95–104. DOI: 10.11835/j.issn.1000-582X.2019.07.011. [15] HASSAN A R, SUBASI A, ZHANG Y C. Epilepsy seizure detection using complete ensemble empirical mode decomposition with adaptive noise [J]. Knowledge-Based Systems, 2020, 191: 105333. DOI: 10.1016/j.knosys.2019.105333. [16] HE C B, NIU P, YANG R, et al. Incipient rolling element bearing weak fault feature extraction based on adaptive second-order stochastic resonance incorporated by mode decomposition [J]. Measurement, 2019, 145: 687–701. DOI: 10.1016/j.measurement.2019.05.052. [17] LI L, WANG F, SHANG F, et al. Energy spectrum analysis of blast waves based on an improved Hilbert–Huang transform [J]. Shock Waves, 2017, 27(3): 487–494. DOI: 10.1007/s00193-016-0667-7. [18] 王明同. 基于小波包分析法的电压暂降检测研究与LabVIEW实现[D]. 广州: 华南理工大学, 2013. [19] 李洪涛. 基于能量原理的爆破地震效应研究[D]. 武汉: 武汉大学, 2007. [20] 王海龙, 赵岩, 王永佳, 等. 草帽山隧道爆破振动监测与分析 [J]. 铁道建筑, 2017, 57(12): 67–70. DOI: 10.3969/j.issn.1003-1995.2017.12.18.WANG H L, ZHAO Y, WANG Y J, et al. Blasting vibration monitoring and analysis of caomaoshan tunnel [J]. Railway Engineering, 2017, 57(12): 67–70. DOI: 10.3969/j.issn.1003-1995.2017.12.18. [21] 王海龙, 赵岩, 王永佳, 等. 新建京张高铁立体交叉隧道爆破振动控制研究 [J]. 铁道标准设计, 2018, 62(7): 130–134. DOI: 10.13238/j.issn.1004-2954.201710120003.WANG H L, ZHAO Y, WANG Y J, et al. Study on blasting vibration control of three-dimensional cross tunnel on Beijing to Zhangjiakou high-speed railway [J]. Railway Standard Design, 2018, 62(7): 130–134. DOI: 10.13238/j.issn.1004-2954.201710120003. [22] 黄金, 吴庆良, 陈钒. 基于CEEMDAN-WPT联合去噪的灾后求救信号能量分布特征研究 [J]. 南京理工大学学报, 2020, 44(2): 194–201. DOI: 10.14177/j.cnki.32-1397n.2020.44.02.010.HUANG J, WU Q L, CHEN F. Study on energy distribution character about post-disaster rescue signal based on CEEMDAN-WPT denoising [J]. Journal of Nanjing University of Science and Technology, 2020, 44(2): 194–201. DOI: 10.14177/j.cnki.32-1397n.2020.44.02.010. [23] 李火坤, 刘世立, 魏博文, 等. 基于方差贡献率的泄流结构多测点动态响应融合方法研究 [J]. 振动与冲击, 2015, 34(19): 181–191. DOI: 10.13465/j.cnki.Jvs.2015.19.029.LI H K, LIU S L, WEI B W, et al. Multi-point dynamic response data fusion method for a flood discharge structure based on variance dedication rate [J]. Journal of Vibration and Shock, 2015, 34(19): 181–191. DOI: 10.13465/j.cnki.Jvs.2015.19.029. [24] SIMAR L, ZELENYUK V. Improving finite sample approximation by central limit theorems for estimates from Data Envelopment Analysis [J]. European Journal of Operational Research, 2020, 284(3): 1002–1015. DOI: 10.1016/j.ejor.2020.01.036. [25] 谢德红, 李俊锋, 刘菂, 等. 基于改进Hodrick-Prescott分解模型的近红外自适应降噪方法 [J]. 光谱学与光谱分析, 2020, 40(5): 1650–1655. DOI: 10.3964/j.issn.1000-0593(2020)05-1650-06.XIE D H, LI J F, LIU D, et al. An Improved Hodrick-Prescott decomposition based near-infrared adaptive denoising method [J]. Spectroscopy and Spectral Analysis, 2020, 40(5): 1650–1655. DOI: 10.3964/j.issn.1000-0593(2020)05-1650-06. [26] 李宗春, 邓勇, 张冠宇, 等. 变形测量异常数据处理中小波变换最佳级数的确定 [J]. 武汉大学学报 (信息科学版), 2011, 36(3): 285–288. DOI: 10.13203/j.whugis2011.03.006.LI Z C, DEND Y, ZHANG G Y, et al. Determination of best grading of wavelet transform in deformation measurement data filtering [J]. Geomatics and Information Science of Wuhan University, 2011, 36(3): 285–288. DOI: 10.13203/j.whugis2011.03.006. [27] HUANG D, CUI S, LI X Q. Wavelet packet analysis of blasting vibration signal of mountain tunnel [J]. Soil Dynamics and Earthquake Engineering, 2019, 117: 72–80. DOI: 10.1016/j.soildyn.2018.11.025. -
图(11) / 表(3)
计量
- 文章访问数: 727
- HTML全文浏览量: 324
- PDF下载量: 79
- 被引次数: 0