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Article(id=1241777710259831179, tenantId=1146029695717560320, journalId=1240670690148397066, issueId=1241777699996368955, articleNumber=null, orderNo=null, doi=10.3963/j.issn.1001-487X.2024.02.024, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1694102400000, receivedDateStr=2023-09-08, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773992477240, onlineDateStr=2026-03-20, pubDate=1717171200000, pubDateStr=2024-06-01, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773992477240, onlineIssueDateStr=2026-03-20, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773992477240, creator=13701087609, updateTime=1773992477240, updator=13701087609, issue=Issue{id=1241777699996368955, tenantId=1146029695717560320, journalId=1240670690148397066, year='2024', volume='41', issue='2', pageStart='1', pageEnd='252', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773992474792, creator=13701087609, updateTime=1773992784144, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1241778997575619516, tenantId=1146029695717560320, journalId=1240670690148397066, issueId=1241777699996368955, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1241778997575619517, tenantId=1146029695717560320, journalId=1240670690148397066, issueId=1241777699996368955, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=194, endPage=202, ext={EN=ArticleExt(id=1241777710758953375, articleId=1241777710259831179, tenantId=1146029695717560320, journalId=1240670690148397066, language=EN, title=Study on Attenuation Law of Blasting Vibration in a Small Clear Distance Highway Tunnel, columnId=1240702076553065119, journalTitle=Blasting, columnName=BLASTING SAFETY, runingTitle=null, highlight=null, articleAbstract=

In order to study the vibration response of the interlaid rock in the small clear distance tunnel under the blasting load, a field blasting vibration test was carried out based on the blasting project of the Xiaolongmen tunnel. The improved variational mode decomposition (VMD) and multi-scale permutation entropy (MPE) algorithm were employed to denoise the blasting vibration signal. Subsequently, the differences in vibration characteristics between the left arch waist (non-interlaid rock area) and right arch waist (interlaid rock area) of the tunnel were analyzed, along with a comparison and analysis of seismic wave attenuation characteristics generated by cut hole blasting and surrounding hole blasting. The results demonstrate that the improved adaptive VMD-MPE algorithm enables automatic determination of modal number K and penalty factor α while effectively eliminating noise from the vibration signal, reducing subjective decision-making influence. During posterior excavation tunnel face blasting, interlaid rock exhibits significant amplification effects on blast vibrations. Peak particle velocity (PPV) values are higher in interlaid rock compared to non-interlaid areas. However, vibrations attenuate faster within interlaid rock regions. Additionally, analysis reveals that low-frequency vibrations below 40 Hz account for a substantial proportion of energy within interlaid rock areas when comparing frequency characteristics at measuring points between non-interlaid and interlaid regions. Attention should be given to these low-frequency vibrations as they are more likely to induce resonance in supporting structures, posing higher risks of damage or destruction within interlaid rock zones. By analyzing the blasting vibration characteristics of the cut hole and the surrounding hole, it can be found that the vibration velocity generated by the surrounding hole blasting in the surrounding rock behind the tunnel face is greater than that of the cut hole blasting within the range of the scale distance (SD) which is less than or equal to 11.57 m kg1/3 due to the effect of 'corner weakening' and the influence of the seismic wave propagation path. After exceeding the critical value of SD, the vibration velocity generated by the cut hole blasting is greater.

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GAO Wen-xue (1962-), male, born in Xiantao City, Hubei Province, professor, doctoral degree, mainly engaged in scientific research in fields such as mining and rock blasting, underground engineering, etc., (E-mail) .
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为了研究爆破荷载作用下小净距隧道中夹岩区的动力稳定性问题，依托小龙门隧道爆破工程，开展了现场爆破振动监测试验。通过改进的变分模态分解（variational mode decomposition，VMD）与多尺度排列熵（multi-scale permutation entropy，MPE）算法对爆破振动信号进行消噪处理，基于此分析了掏槽孔与周边孔爆破在后行洞左拱腰（非中夹岩区）、右拱腰（中夹岩区）中产生的振动特征差异。结果表明：采用改进的自适应VMD-MPE算法可以有效消除振动信号中的噪声，并降低了主观决策的影响；此外，相对于非中夹岩区，中夹岩对爆破振动具有明显的放大效应，其质点峰值振速明显大于非中夹岩区，但中夹岩区的振动衰减速度更快；同时，通过对比非中夹岩区与中夹岩区各测点振动频率特征可以发现，中夹岩区小于40 Hz的低频振动能量占比较大，更易引起支护结构的共振，发生损伤与破坏的风险更高，应重点关注；受“转角削弱”作用以及地震波传播路径的影响，在比例距离SD小于等于11.57 m·kg1/3范围内，周边孔爆破在掌子面后方围岩中产生的振速大于掏槽孔。

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高文学（1962-），男，湖北省仙桃市人，教授、博士，从事矿岩爆破、地下工程等领域的科研工作，（E-mail）。
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李小帅（1994-），男，河北省定州市人，博士研究生，从事矿岩爆破、地下工程等领域的科研工作，（E-mail）。

LI Xiao-shuai (1994-), male, born in Dingzhou City, Hebei Province, doctoral candidate, mainly engaged in scientific research in fields such as mining and rock blasting, underground engineering, etc., (E-mail) .

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李小帅（1994-），男，河北省定州市人，博士研究生，从事矿岩爆破、地下工程等领域的科研工作，（E-mail）。

LI Xiao-shuai (1994-), male, born in Dingzhou City, Hebei Province, doctoral candidate, mainly engaged in scientific research in fields such as mining and rock blasting, underground engineering, etc., (E-mail) .

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李小帅（1994-），男，河北省定州市人，博士研究生，从事矿岩爆破、地下工程等领域的科研工作，（E-mail）。

LI Xiao-shuai (1994-), male, born in Dingzhou City, Hebei Province, doctoral candidate, mainly engaged in scientific research in fields such as mining and rock blasting, underground engineering, etc., (E-mail) .

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point, figureFileSmall=Kq6A1u/8c7afe9VYk8RmTQ==, figureFileBig=Nl/qg/NkagP9zXl/KkkUgQ==, tableContent=null), ArticleFig(id=1241777727586500857, tenantId=1146029695717560320, journalId=1240670690148397066, articleId=1241777710259831179, language=CN, label=图10, caption=各测点爆破振动频率分布图, figureFileSmall=Kq6A1u/8c7afe9VYk8RmTQ==, figureFileBig=Nl/qg/NkagP9zXl/KkkUgQ==, tableContent=null), ArticleFig(id=1241777727716524286, tenantId=1146029695717560320, journalId=1240670690148397066, articleId=1241777710259831179, language=EN, label=Table 1, caption=

Upper bench blasting parameters

, figureFileSmall=null, figureFileBig=null, tableContent=
序号炮孔类型孔数孔径/mm起爆时间/ms单孔装药量/kg孔深/m累计装药/kg
1掏槽孔842.0　0.02.73.521.6
2扩槽孔842.050.02.43.219.2
3辅助孔1242.0100.01.83.021.6
4辅助孔1542.0150.01.83.027.0
5辅助孔1842.0200.01.83.032.4
6内圈孔2642.0250.01.53.039.0
7周边孔4542.0300.00.93.040.5
合计 132    201.3
), ArticleFig(id=1241777727833964802, tenantId=1146029695717560320, journalId=1240670690148397066, articleId=1241777710259831179, language=CN, label=表1, caption=

上台阶爆破参数

, figureFileSmall=null, figureFileBig=null, tableContent=
序号炮孔类型孔数孔径/mm起爆时间/ms单孔装药量/kg孔深/m累计装药/kg
1掏槽孔842.0　0.02.73.521.6
2扩槽孔842.050.02.43.219.2
3辅助孔1242.0100.01.83.021.6
4辅助孔1542.0150.01.83.027.0
5辅助孔1842.0200.01.83.032.4
6内圈孔2642.0250.01.53.039.0
7周边孔4542.0300.00.93.040.5
合计 132    201.3
), ArticleFig(id=1241777727943016708, tenantId=1146029695717560320, journalId=1240670690148397066, articleId=1241777710259831179, language=EN, label=Table 2, caption=

Energy change rate of different K values

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模态数K值2345678
能量变化率η0.103860.103890.110880.111480.111740.188900.22824
|ηk+1-ηk| 0.000030.006990.000600.000260.077160.03934-
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不同K值能量变化率

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模态数K值2345678
能量变化率η0.103860.103890.110880.111480.111740.188900.22824
|ηk+1-ηk| 0.000030.006990.000600.000260.077160.03934-
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The MPE mean of IMF component

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分量 IMF1 IMF2 IMF3 IMF4 IMF5 IMF6
MPE0.529600.600200.663100.797300.949000.96130
互相关系数R0.822500.535500.475400.127400.033600.02740
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IMF分量的MPE均值

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分量 IMF1 IMF2 IMF3 IMF4 IMF5 IMF6
MPE0.529600.600200.663100.797300.949000.96130
互相关系数R0.822500.535500.475400.127400.033600.02740
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小净距隧道掘进爆破及其振动响应规律研究
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李小帅 1 , 高文学 1 , 宿利平 2 , 张小军 1 , 胡宇 1 , 薛睿 1
爆破 | 安全与管理 2024,41(2): 194-202
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爆破 | 安全与管理 2024, 41(2): 194-202
小净距隧道掘进爆破及其振动响应规律研究
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李小帅1 , 高文学1 , 宿利平2, 张小军1, 胡宇1, 薛睿1
作者信息
  • 1.北京工业大学　城市建设学部，北京　100124
  • 2.北京市政路桥股份有限公司，北京　100045

    • 李小帅（1994-），男，河北省定州市人，博士研究生，从事矿岩爆破、地下工程等领域的科研工作，（E-mail）。

    LI Xiao-shuai (1994-), male, born in Dingzhou City, Hebei Province, doctoral candidate, mainly engaged in scientific research in fields such as mining and rock blasting, underground engineering, etc., (E-mail) .

通讯作者:

高文学（1962-），男，湖北省仙桃市人，教授、博士，从事矿岩爆破、地下工程等领域的科研工作，（E-mail）。
Study on Attenuation Law of Blasting Vibration in a Small Clear Distance Highway Tunnel
Xiao-shuai LI1 , Wen-xue GAO1 , Li-ping SU2, Xiao-jun ZHANG1, Yu HU1, Rui XUE1
Affiliations
  • 1.Faculty of Architecture, Civil and Transportation Engineering, Beijing University of Technology, Beijing 100124, China
  • 2.Beijing Municipal Road and Bridge Co., Ltd., Beijing 100045, China
出版时间: 2024-06-01 doi: 10.3963/j.issn.1001-487X.2024.02.024
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摘要
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为了研究爆破荷载作用下小净距隧道中夹岩区的动力稳定性问题，依托小龙门隧道爆破工程，开展了现场爆破振动监测试验。通过改进的变分模态分解（variational mode decomposition，VMD）与多尺度排列熵（multi-scale permutation entropy，MPE）算法对爆破振动信号进行消噪处理，基于此分析了掏槽孔与周边孔爆破在后行洞左拱腰（非中夹岩区）、右拱腰（中夹岩区）中产生的振动特征差异。结果表明：采用改进的自适应VMD-MPE算法可以有效消除振动信号中的噪声，并降低了主观决策的影响；此外，相对于非中夹岩区，中夹岩对爆破振动具有明显的放大效应，其质点峰值振速明显大于非中夹岩区，但中夹岩区的振动衰减速度更快；同时，通过对比非中夹岩区与中夹岩区各测点振动频率特征可以发现，中夹岩区小于40 Hz的低频振动能量占比较大，更易引起支护结构的共振，发生损伤与破坏的风险更高，应重点关注；受“转角削弱”作用以及地震波传播路径的影响，在比例距离SD小于等于11.57 m·kg1/3范围内，周边孔爆破在掌子面后方围岩中产生的振速大于掏槽孔。

中夹岩  /  小净距隧道  /  爆破振动效应  /  变分模态分解  /  多尺度排列熵

In order to study the vibration response of the interlaid rock in the small clear distance tunnel under the blasting load, a field blasting vibration test was carried out based on the blasting project of the Xiaolongmen tunnel. The improved variational mode decomposition (VMD) and multi-scale permutation entropy (MPE) algorithm were employed to denoise the blasting vibration signal. Subsequently, the differences in vibration characteristics between the left arch waist (non-interlaid rock area) and right arch waist (interlaid rock area) of the tunnel were analyzed, along with a comparison and analysis of seismic wave attenuation characteristics generated by cut hole blasting and surrounding hole blasting. The results demonstrate that the improved adaptive VMD-MPE algorithm enables automatic determination of modal number K and penalty factor α while effectively eliminating noise from the vibration signal, reducing subjective decision-making influence. During posterior excavation tunnel face blasting, interlaid rock exhibits significant amplification effects on blast vibrations. Peak particle velocity (PPV) values are higher in interlaid rock compared to non-interlaid areas. However, vibrations attenuate faster within interlaid rock regions. Additionally, analysis reveals that low-frequency vibrations below 40 Hz account for a substantial proportion of energy within interlaid rock areas when comparing frequency characteristics at measuring points between non-interlaid and interlaid regions. Attention should be given to these low-frequency vibrations as they are more likely to induce resonance in supporting structures, posing higher risks of damage or destruction within interlaid rock zones. By analyzing the blasting vibration characteristics of the cut hole and the surrounding hole, it can be found that the vibration velocity generated by the surrounding hole blasting in the surrounding rock behind the tunnel face is greater than that of the cut hole blasting within the range of the scale distance (SD) which is less than or equal to 11.57 m kg1/3 due to the effect of 'corner weakening' and the influence of the seismic wave propagation path. After exceeding the critical value of SD, the vibration velocity generated by the cut hole blasting is greater.

interlaid rock  /  small clear distance tunnel  /  blasting vibration effect  /  variational mode decomposition  /  multi-scale permutation entropy
李小帅, 高文学, 宿利平, 张小军, 胡宇, 薛睿. 小净距隧道掘进爆破及其振动响应规律研究. 爆破, 2024 , 41 (2) : 194 -202 . DOI: 10.3963/j.issn.1001-487X.2024.02.024
Xiao-shuai LI, Wen-xue GAO, Li-ping SU, Xiao-jun ZHANG, Yu HU, Rui XUE. Study on Attenuation Law of Blasting Vibration in a Small Clear Distance Highway Tunnel[J]. Blasting, 2024 , 41 (2) : 194 -202 . DOI: 10.3963/j.issn.1001-487X.2024.02.024
正文
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随着我国公路、铁路隧道大规模建设，小净距隧道工程不断涌现。中夹岩作为小净距隧道的重要承载结构，其在爆破荷载作用下的稳定性对于保证隧道施工安全至关重要[1-3]。
爆破振动作为影响隧道中夹岩稳定性的重要因素之一，得到了相关研究人员的广泛关注。DENG Tao等模拟狮子山隧道爆破掘进过程[4]，分析了中夹岩的振动衰减规律，得到了中夹岩在三个方向振动速度的分布特征。罗阳等针对小净距隧道后行洞爆破施工所引起的先行洞围岩振动问题[5]，研究了中夹岩厚度与先行洞迎爆侧最大振速的关系。刘传阳等对比分析了掏槽爆破、光面爆破对中夹岩的振动影响[6]，发现中夹岩的峰值振速比掌子面前方区域放大1.4倍；通过分析振动波形提出了降低爆破振速、提高爆破循环进尺的技术措施。以上学者针对小净距隧道爆破振动响应特性的研究主要聚焦于后行洞爆破对先行洞迎爆侧的影响，并且大部分研究仅从爆破振动速度衰减规律方面分析隧道掘进爆破对中夹岩的扰动影响，缺乏从爆破振动能量特征、频率特性以及地震波传播规律等角度，分析后行洞爆破振动对中夹岩区与非中夹岩区的影响差异。此外，受隧道施工环境复杂性、电磁干扰等因素影响，所测得的原始振动信号往往会携带大量的高频噪声，为获取更为真实的振动信号必须采取降噪处理。目前，针对爆破振动信号常用的降噪算法包括经典模态分解算法（EMD）、小波类算法以及EMD改进类算法等[7-12]。虽然这些算法能够在一定程度上满足剔除噪声的要求，但仍存在模态混叠、主观决策以及端点效应等问题。
为优化爆破振动信号降噪处理效果，并进一步掌握小净距隧道后行洞爆破振动对中夹岩的影响规律，本文引入了改进的自适应VMD-MPE算法，并以国道109新线高速小龙门隧道工程为背景，开展爆破振动现场监测试验，对比分析不同类型炮孔爆破在掌子面后方中夹岩区以及非中夹岩区的振动速度衰减规律、频率分布特征以及地震波的传播规律，研究成果可为小净距隧道爆破振动控制提供指导与参考。
1　工程概况及振动监测
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1.1　工程概况
国道109新线高速小龙门隧道位于北京、河北交界处，全长6412 m，隧道（北京段）起止桩号为A1K73+999.38~A1K78+377。该隧道为双向分离式4车道，开挖宽度16.84 m，开挖高度11.25 m，相邻隧道净距为20.8 m，根据《公路隧道设计规范》（JTG D70—2004）属于小净距隧道[13]。爆破振动监测段范围为A1K74+715~A1K74+765，该范围内围岩等级主要为III级，多为白云质灰岩，埋深206 m，采用上下台阶法钻爆施工，炸药类型为2#岩石乳化炸药，药卷直径32 mm，爆速为3600 m/s，密度为1300 kg/m3，使用数码电子雷管起爆。隧道爆破上台阶炮孔布置如图1、爆破参数如表1所示。
1.2　监测方案
为监测后行洞掌子面爆破引起的振动响应情况，在后行洞上台阶的左拱腰、右拱腰（中夹岩区）各布置3个监测点，#1和#4监测点距爆破掌子面30 m，同侧监测点间距为10 m，监测点距离地面高度约为1.5 m，监测点位置如图2所示。
现场监测采用TC-6850爆破测振仪，其速度量程为0~25 cm/s，测振频带范围为5~300 Hz，采样率6.4 kSps。传感器的X、Y、Z分别指向隧道的纵向、横断面方向与垂向。同时，为了防止飞石及冲击波影响监测数据，在仪器周围固定金属防护罩，如图3所示。
2　信号主成分分量提取
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2.1　改进的自适应VMD-MPE原理
VMD算法作为一种完全非递归的自适应信号处理方法，克服了EMD算法的模态混叠问题与小波算法自适应性差的问题。本研究提出的改进的自适应VMD-MPE算法，是在VMD算法基础上，通过迭代计算重构信号与原始信号能量差，并借助粒子群优化算法（Particle Swarm Optimization，PSO）求取最大信噪比SNR，以此自动研判VMD的模态数K值与惩罚因子α，并通过MPE算法进行随机性检测，从而避免频率混叠或过分解，达到降噪的目的。
改进的自适应VMD-MPE信号处理过程包括：分解原始信号[14]、确定模态信号带宽[15]、求取非约束变分问题最优解[16,17]、确定合适的模态数K值与惩罚因子α值、MPE处理等过程[18]。
在传统VMD-MPE算法中，K值与α值通常由人为自主设定，本研究通过标定VMD处理后的信号能量变化率η与信噪比SNR，公式（1）~（4），自动确定K值与α值，以降低人为因素对信号分解效果的影响。根据文献[19]的研究，当模态数为K+1的信号能量变化率ηk+1与模态数为K的信号能量变化率ηk之差超过某一阈值时，信号处于过分解状态，因此可以确定此时的模态数K为最佳。本研究通过多次试算，当ηk+1与ηk差值超过0.06时，K值最佳。根据文献[20]，SNR值越大，可保留更多的原始信号特征，则SNR最大值所对应的α值为最佳。
式中：E为爆破振动原始信号能量；f（t）为原始信号；uk（t）为模态函数分量；Ek为第K个模态函数分量的能量；x（t）为离散时间信号序列；t0信号为起始点；T为信号采集长度。
式中，为经VMD处理后重构信号时间为t时的采样点值。
2.2　VMD-MPE分解与重构
使用自适应VMD-MPE算法对现场监测爆破振动信号进行处理。以一条典型爆破振动信号#1测点Y方向为例（图4），分析该算法的消噪效果。表2为该振动信号分解为不同数量模态分量时的能量变化率η与。由表2可以看出，当K值由6增加到7时，信号能量变化率η出现较大幅度的增长，超过0.06，信号处于过分解状态，由此可以确定该信号被分解为6个模态分量为最佳，同时借助PSO算法，确定α值为1000。
图5为分解得到的6个IMF分量（IMF1~IMF6），从图中可以看出，各个IMF分量曲线光滑，时间尺度区分明显，且伴随着频率由低到高进行排列。这说明自适应VMD-MPE算法可以有效避免各IMF分量之间的模态混叠问题。与此同时，IMF4~IMF6的中心频率较高，且其幅值远低于IMF1~IMF3，由此可以推断IMF4~IMF6极大可能为混入的高频噪声信号。结合各IMF分量的MPE值以及各IMF分量与原信号的互相关系数R（表3）可以进一步准确地识别出噪声分量，IMF4~IMF6的MPE值均超过设定阈值0.7，且IMF~IMF6与原信号的相关性处于较低水平，因此可以确定IMF4~IMF6为噪声。将噪声剔除后的真实爆破振动信号如图4所示，可以看出重构信号与原始信号波形一致，局部突出噪声得到有效消除，且没有出现明显的“削峰”现象，重构信号有效保留了真实爆破振动信号的信息。
3　爆破振动规律研究
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3.1　爆破振动波形特征
现场共进行了5次爆破振动监测试验，并将得到的原始数据进行自适应VMD-MPE消噪处理。由于篇幅所限，仅列出距爆破掌子面30 m处隧道左拱腰（#1）与中夹岩（#4）典型爆破振动时程曲线，如图6所示。图中按数码电子雷管延期时间划分了不同段别炮孔爆破振动曲线。通过图6可以发现，各段波形虽然存在一定叠加，但整体分界清晰，各段波形起波时间与设定吻合。对比左拱腰与中夹岩三向波形图可以看出，除极少数段别外，绝大多数段别爆破在中夹岩一侧所引起的振动大于左拱腰。此外，两个测点的X与Z方向最大质点峰值振速出现在第7个波峰处，Y方向最大质点峰值振速出现在第1个波峰处，同时通过计算三向振动合速度最大值出现在第7个波峰处，第1个波峰峰值次之，但两者相差较小，这说明在距掌子面30 m处，周边孔爆破产生的振动最大，且略大于掏槽孔爆破所产生的振动。
3.2　隧道左拱腰与中夹岩振动速度衰减特征
为分析爆破作用下后行洞左拱腰与右侧中夹岩的振动速度特征差异，根据萨道夫斯基经验公式，对爆破振动监测数据进行回归分析[21]
式中，α、K、SD、Q与R分别为衰减系数、场地系数、比例距离、单段药量以及测点距爆源的距离。
图7显示了隧道左拱腰与中夹岩各测点质点峰值振速PPV与比例距离SD的关系。通过图7可知，掌子面爆破在中夹岩与左拱腰中产生的振动速度衰减特征存在差异，中夹岩振速衰减拟合曲线的K值与α值均大于左拱腰，这说明在监测范围内的中夹岩振动速度更大，但衰减较快。分析认为，中夹岩存在两个临空面，形成了自由度更大的“薄板结构”，这会在一定程度上产生放大效应，同时沿隧道径向传播的地震波在遇到已开挖隧道时会发生反射，反射波与沿隧道轴线方向传播的地震波会产生叠加这也可能造成振动速度的增大。一般情况下，小净距隧道中夹岩的损伤程度会更严重，地震波在裂隙较多的中夹岩中传播会造成其能量的快速衰减，因此地震波在中夹岩中传播衰减比左拱腰更快。
3.3　掏槽孔与周边孔爆破振动速度衰减特征
图8反映了掏槽孔、周边孔爆破时，中夹岩一侧PPV随SD的变化规律。对比掏槽孔与周边孔爆破振动衰减曲线可知，周边孔爆破产生的振动衰减速率比掏槽孔更快。其原因主要是周边孔爆破时有两个自由面而掏槽孔只有一个，周边孔爆破所受到的岩石夹制作用比掏槽孔弱，并且周边孔爆破时隧道围岩已受到前序多段爆破扰动而产生大量微裂纹，这导致了周边孔爆破所产生的地震波PPV值衰减更快。此外，当SD小于等于11.57 m·kg1/3时，即距爆源较近的一段范围内，周边孔爆破产生的地震波PPV值更大；当SD超过11.57 m·kg1/3时，即距爆源较远后，掏槽孔爆破产生的地震波PPV值更大。从掏槽孔与周边孔的装药量来看，虽然周边孔总装药量远大于掏槽孔，但周边孔分布分散，正常情况下周边孔爆破所引起的PPV值应小于掏槽孔PPV值，然而本研究发现在距离爆源较近时上述规律并不适用。
通过分析两种炮孔爆破所产生地震波的传播路径（图9）可以对上述现象进行解释。由于监测点位于掌子面后方，受开挖空洞影响，爆破产生的地震波无法以直达波的形式传递到监测点处，需要先沿隧道掌子面径向传播至开挖边界后才可沿隧道洞壁传播，此过程会受到转角的削弱作用影响[22]。掏槽孔位于掌子面中间位置，距离开挖轮廓线有一定距离（本研究约6.8 m），存在覆盖面积较大的转角区域，同时传播路径长度相对更长，这导致地震波的幅值被较大程度削弱，而周边孔紧邻开挖轮廓线，转角的削弱作用可以忽略不计并且传播路径相对较近，因此在距掌子面一定范围内周边孔的PPV值大于掏槽孔。但由于周边孔产生的地震波衰减速率更快，且距离掌子面较远后转角的削弱作用以及传播路径长度对地震波的衰减影响减弱，因此在超过SD临界值后，掏槽孔PPV值大于周边孔。
3.4　爆破振动频率分析
在评估爆破振动危害程度时，振动频率也是一个重要参考因素[23]。图10显示了隧道左拱腰及中夹岩爆破振动频率分布情况。可以看出，距离掌子面较近的监测点振动高频率部分分布范围更广，其中测点#1与#4的频率范围最广，主要分布在20~120 Hz范围内，而其他监测点的频率主要分布在20~80 Hz范围内。这是由于含缺陷岩体会以不同的速率抑制或衰减地震波频率，通常情况下，岩石对高频率波的衰减作用大于对低频率波[24]，高频率波在岩石中传播时需要更多的运动周期来通过相同的距离，因此高频率波比低频率波的衰减速率更快。
对比隧道左拱腰与中夹岩频率分布情况可以发现，两者频率成分存在较大差异。隧道左拱腰#1~#3监测点小于40 Hz低频段的边际能量占比分别为24.03%、29.64%、30.10%，中夹岩#4~#6监测点小于40 Hz低频段的边际能量占比分别为39.57%、56.63%、60.23%。由此可见，中夹岩一侧低频振动能量占比较大。由于低频振动更容易引起结构的共振，其对隧道的安全影响更大[25]，再加上中夹岩对爆破振动速度的放大效应，中夹岩一侧的围岩与衬砌结构出现损伤与破坏的风险更高，因此在隧道爆破施工过程中应重点关注中夹岩的稳定性。
4　结论
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针对爆破荷载作用下小净距隧道中夹岩的动力稳定性问题，采用现场监测的手段，研究了掏槽孔、周边孔爆破在隧道不同区域产生的振动规律，并且通过改进自适应VMD-MPE算法，对实测振动信号中的噪声进行了处理，主要得出以下结论：
（1）改进的自适应VMD-MPE算法，实现了模态数K与惩罚因子α的自动研判，避免了主观决策的干扰，同时该算法可以有效解决信号分解时模态混叠与过分解的问题，能够准确剔除噪声信号从而达到降噪的目的。
（2）小净距隧道后行洞爆破在中夹岩一侧拱腰处产生的振动大于另一侧拱腰，地震波在中夹岩中传播存在明显的放大效应，但中夹岩区的振动衰减速率较快。
（3）以比例距离SD=11.57 m·kg1/3为临界值，在SD≤11.57 m·kg1/3范围内，周边孔爆破在掌子面后方围岩中的产生的振动大于掏槽孔，但超过该比例距离临界值后，掏槽孔爆破所产生的振动会逐渐超过周边孔。
（4）岩石的高频滤波特性导致爆破振动频率范围随比例距离的增大而减小，高频只出现在爆破近区；中夹岩一侧小于40 Hz的低频振动能量占比较大，更易引起围岩与支护结构的共振，发生破坏的风险更高。
基金
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  • 爆破工程湖北省重点实验室开放基金(BL2021-23)
文献
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2024年第41卷第2期
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doi: 10.3963/j.issn.1001-487X.2024.02.024
  • 接收时间：2023-09-08
  • 首发时间：2026-03-20
  • 出版时间：2024-06-01
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  • 收稿日期：2023-09-08
基金
Hubei Provincial Key Laboratory Open Fund for Blasting Engineering(BL2021-23)
爆破工程湖北省重点实验室开放基金(BL2021-23)
作者信息
    1.北京工业大学　城市建设学部，北京　100124
    2.北京市政路桥股份有限公司，北京　100045

通讯作者:

高文学（1962-），男，湖北省仙桃市人，教授、博士，从事矿岩爆破、地下工程等领域的科研工作，（E-mail）。
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https://castjournals.cast.org.cn/joweb/bp/CN/10.3963/j.issn.1001-487X.2024.02.024
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2种不同金属材料的力学参数
科
Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
Genus		 种数
Number of
species		 占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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