冻结立井爆破近区井壁振动信号基线漂移校正和消噪方法

付晓强; 杨仁树; 刘纪峰; 张会芝; 张仁巍

doi:10.11883/bzycj-2019-0367

冻结立井爆破近区井壁振动信号基线漂移校正和消噪方法

doi: 10.11883/bzycj-2019-0367

付晓强^{1, 2,},
杨仁树³,
刘纪峰^{1, 2},
张会芝^{1, 2},
张仁巍^{1, 2}

1.
三明学院建筑工程学院，福建三明 365004
2.
三明学院工程材料与结构加固福建省高等学校重点实验室，福建三明 365004
3.
北京科技大学土木与资源工程学院，北京 100083

基金项目: 三明学院引进高层次人才科研启动经费（18YG13）

详细信息

作者简介:
付晓强（1984－　），男，博士，讲师，fuxiaoqiang1984@163.com

中图分类号: O389; TD235.1
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- 被引次数: 0
出版历程
- 收稿日期: 2019-09-23
- 修回日期: 2020-02-11
- 网络出版日期: 2020-08-25
- 刊出日期: 2020-09-01

Baseline drift correction and de-noising method of shaft lining vibration signal in near field of freezing vertical shaft blasting

FU Xiaoqiang^{1, 2
,},
YANG Renshu³,
LIU Jifeng^{1, 2},
ZHANG Huizhi^{1, 2},
ZHANG Renwei^{1, 2}

1.
School of Civil Engineering, Sanming University, Sanming 365004, Fujian, China
2.
Key Laboratory of Engineering Material & Structure Reinforcement in Fujian Province College, Sanming University, Sanming 365004, Fujian, China
3.
School of Civil and Resources Engineering, University of Science and Technology Beijing, Beijing 100083, China

摘要

摘要: 冻结立井爆破过程中，近区监测信号中含有的基线漂零及噪声成分对其局部特征精细化提取影响显著。在对近区井壁振动信号有效采集基础上，通过互补总体经验模态分解（complementary ensemble empirical mode decomposition, CEEMD）方法、稀疏化基线估计消噪（baseline estimation and de-noising with sparsity, BEADS）方法和隐马尔可夫模型消噪（hidden Markov model de-noising, HMMD）方法等，解决了信号中基线漂移和随机噪声消除难题，并采用交叉小波变换对校正和消噪效果进行了相关性评价。实例分析结果表明：信号中缓变的基线成分遍历信号各个模态分量的整个过程，且主要集中于低频分量中，而噪声则集中在高频分量。组合分析方法对低频基线漂零和高频噪声的处理效果好，是一种高效且相对保幅的信号分析方法，可用于批量信号数据的预处理过程。
- 冻结立井 /
- 爆破振动 /
- 基线偏移 /
- 消噪分析 /
- 交叉小波变换 /
- 相关性分析
Abstract: In the process of freezing vertical shaft blasting, the baseline drift and noise in the near area monitoring signal have significant influence on the fine extraction of local characteristics. On the basis of effective acquisition of shaft lining vibration signals in near field of blasting, complementary ensemble empirical mode decomposition (CEEMD) method, baseline estimation and de-noising with sparsity (BEADS) method and hidden Markov model de-noising (HMMD) method and so on are used to solve the problem of baseline drift and random noise elimination in the signal, and the correlation evaluation of correction and noise elimination effect is carried out by cross wavelet transform (CWT). The analysis results show that: the slowly changing baseline component in the signal exists the whole process of each modal component, and it is mainly concentrated in the low frequency component, while the noise is concentrated in the high frequency component. The combined analysis method can deal with low frequency baseline drift and high frequency noise effectively. It is an efficient and relatively amplitude-preserving signal analysis method, and can be used to preprocess of batch blasting vibration signal data.
- freezing vertical shaft /
- blasting vibration /
- baseline drift /
- de-noising analysis /
- cross wavelet transform /
- correlation analysis

HTML全文

图 1 基线校正及消噪流程

Figure 1. Baseline correction and noise reduction process

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图 2 传感器井壁预埋法

Figure 2. Pre-embedding method of vibration instrument

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图 3 炮眼布置（单位：mm）

Figure 3. Borehole layout (unit: mm)

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图 4 爆破近区井壁振动信号

Figure 4. Vibration signal of shaft lining near blasting area

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图 5 各IMF分量筛分迭代次数关系

Figure 5. The relationship of iterations number and shift number

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图 6 信号CEEMD分解各分量及残余项R

Figure 6. Component of CEEMD decomposition and residual signal

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图 7 模态分量处理结果

Figure 7. Results of baseline correction processing

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图 8 各分量基线成分

Figure 8. Baseline of each component

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图 9 罚函数值与迭代次数关系

Figure 9. Relation of cost function and the iteration number

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图 10 基线校正后信号

Figure 10. Baseline corrected signal

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图 11 CEEMD重构信号

Figure 11. Reconstructed signals of CEEMD

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图 12 消噪后的校正信号

Figure 12. Baseline corrected signal after de-noising

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图 13 信号功率谱密度（w_f）

Figure 13. Power spectral density (w_f) of signal

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图 14 信号相关性凝聚谱

Figure 14. Correlation condensation spectra of signals

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表 1 模态分量与原信号相关度

Table 1. Correlation between components and original signals

IMF 相关性系数 IMF 相关性系数 IMF 相关性系数

1 0.4202 5 0.5023 9 0.1083
2 0.4484 6 0.1419 10 0.3707
3 0.3754 7 0.1333 11 0.4540
4 0.4124 8 0.1364 12 0.2940

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表 2 不同方法消噪性能指标

Table 2. Indexes of noise reduction performance

去噪方法评价指标
SNR RMSE CC PE

MD 3.442 0.581 0.816 1.758
SVD 20.983 0.379 0.896 1.175
WED 21.397 0.374 0.921 0.492
HMMD 43.371 0.056 0.992 0.244

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