Article(id=1241769330380177722, tenantId=1146029695717560320, journalId=1240670690148397066, issueId=1241769329201578292, articleNumber=null, orderNo=null, doi=10.3963/j.issn.1001-487X.2024.01.003, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1656432000000, receivedDateStr=2022-06-29, revisedDate=null, revisedDateStr=null, acceptedDate=null, acceptedDateStr=null, onlineDate=1773990479321, onlineDateStr=2026-03-20, pubDate=1709222400000, pubDateStr=2024-03-01, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1773990479321, onlineIssueDateStr=2026-03-20, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1773990479321, creator=13701087609, updateTime=1773990479321, updator=13701087609, issue=Issue{id=1241769329201578292, tenantId=1146029695717560320, journalId=1240670690148397066, year='2024', volume='41', issue='1', pageStart='1', pageEnd='220', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1773990479040, creator=13701087609, updateTime=1773992264087, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1241776816298459159, tenantId=1146029695717560320, journalId=1240670690148397066, issueId=1241769329201578292, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1241776816298459160, tenantId=1146029695717560320, journalId=1240670690148397066, issueId=1241769329201578292, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=14, endPage=20, ext={EN=ArticleExt(id=1241769330665390395, articleId=1241769330380177722, tenantId=1146029695717560320, journalId=1240670690148397066, language=EN, title=Application of Time-frequency Analysis of Blasting Vibration of Underground Cavern based on CEEMDAN-INHT, columnId=1240702071733801442, journalTitle=Blasting, columnName=THEORETICAL AND TECHNOLOGICAL EXPLORATION, runingTitle=null, highlight=null, articleAbstract=

The seismic wave signal acquisition will result in the mixed noise in the measured signal due to the monitoring environment, test system and other factors, and the existence of noise will lead to the distortion of the time-frequency analysis results of the signal Hilbert-Huang Transform. There are two reasons. One is that the empirical mode decomposition (EMD) algorithm will obtain the intrinsic mode function (IMF) component with modal confusion phenomenon when processing the blasting seismic wave signal containing noise; The other reason is that because the Hilbert transform is constrained by the Bedrosian theorem, which will produce negative instantaneous frequencies when dealing with modal confusion components. These lead to huge analytical errors. In order to obtain real blasting vibration properties, HHT should be improved. Complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) can be obtained by adding adaptive noise signal to EMD. Then normalized Hilbert transform is performed on the IMF obtained by CEEMDAN, and an improved normalized Hilbert transform (INHT) is obtained. Through the above two steps, the CEEMDAN-INHT time-frequency analysis algorithm can be established. In order to verify that the algorithm can effectively improve the time-frequency analysis accuracy of the noise-containing blasting seismic wave vibration signal, a comparative study on the time-frequency analysis of the HHT and CEEMDAN-INHT noise-containing simulated vibration signals is carried out. Finally, CEEMDAN-INHT is used in the time-frequency analysis of blasting seismic wave signals in an underground cavern, and it is found that the algorithm can effectively overcome the inherent mode confusion of EMD, and at the same time obtain the time-frequency-energy characteristic parameters reflecting the real blasting vibration attributes. It is of practical significance to carry out resonance analysis of blasting excavation in caverns from the perspective of frequency and energy, and to realize blasting seismic wave hazard control.

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WU Li (1963-), male, professor, doctoral supervisor, mainly engaged in researching geotechnical and blasting engineering, (E-mail) .
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爆破地震波信号采集会因监测环境、测试系统等因素导致实测信号中混有噪声,噪声的存在将导致信号希尔伯特-黄变换(Hilbert-Huang Transform,HHT)时频分析结果失真。原因有二:其一是经验模态分解(Ensemble Empirical Mode,EMD)处理含噪爆破地震波信号会得到具有模态混淆现象的固有模态函数(Intrinsic mode function,IMF)分量;其二是Hilbert变换受Bedrosian定理的约束在处理模态混淆分量时会产生负值瞬时频率,从而造成巨大的分析误差。为获得真实的爆破振动属性需对HHT进行改进,在EMD中添加自适应噪声信号得到自适应补充集合经验模态分解(Complete Ensemble Empirical Mode Decomposition with A-daptive Noise,CEEMDAN)算法;再对CEEMDAN得到的IMF进行归一化Hilbert变换,得到改进归一化Hilbert变换(Improved Normalized Hilbert Transform,INHT)。通过上述两步可建立CEEMDAN-INHT时频分析算法,为验证该算法可有效提高含噪爆破地震波振动信号时频分析精度,进行HHT和CEEMDAN-INHT含噪仿真振动信号时频分析对比研究。最后将CEEMDAN-INHT用于某地下洞室爆破地震波信号时频分析中,发现该算法能有效克服EMD固有的模态混淆现象,同时得到反映真实爆破振动属性的时-频-能特征参数,对从频率-能量的角度进行洞室爆破开挖共振分析,实现爆破地震波危害控制具有一定的现实意义。

, correspAuthors=null, authorNote=null, correspAuthorsNote=
吴立(1963-),男,教授、博士生导师,主要研究岩土与爆破工程,(E-mail)
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孙苗(1993-),女,讲师,主要从事改进HHT算法爆破地震波信号处理,(E-mail)

SUN Miao (1993-), female, lecturer, mainly engaged in improved HHT algorithm for processing blasting seismic wave signals, (E-mail) .

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孙苗(1993-),女,讲师,主要从事改进HHT算法爆破地震波信号处理,(E-mail)

SUN Miao (1993-), female, lecturer, mainly engaged in improved HHT algorithm for processing blasting seismic wave signals, (E-mail) .

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孙苗(1993-),女,讲师,主要从事改进HHT算法爆破地震波信号处理,(E-mail)

SUN Miao (1993-), female, lecturer, mainly engaged in improved HHT algorithm for processing blasting seismic wave signals, (E-mail) .

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figureFileBig=til8zIHNzL0gXVZdPsPI0w==, tableContent=null), ArticleFig(id=1241769349611061369, tenantId=1146029695717560320, journalId=1240670690148397066, articleId=1241769330380177722, language=CN, label=图12, caption=IMF边际谱, figureFileSmall=INuMfg896wlHf+WOy/4tlA==, figureFileBig=til8zIHNzL0gXVZdPsPI0w==, tableContent=null), ArticleFig(id=1241769349703336060, tenantId=1146029695717560320, journalId=1240670690148397066, articleId=1241769330380177722, language=EN, label=Table 1, caption=

Energy values of typical seismic wave signals in each frequency band

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频带0~100 Hz100~200 Hz200~400 Hz400~800 Hz>800 Hz
能量大小径向0.291×10-40.235×10-30.682×10-30.973×10-32.351×10-3
纵向0.527×10-50.314×10-40.414×10-41.863×10-44.418×10-4
垂向0.536×10-50.367×10-40.549×10-41.926×10-45.156×10-4
各频带能量汇总3.973×10-53.031×10-47.783×10-41.288×10-33.308×10-3
占总能量比率0.695%5.302%13.613%22.529%57.861%
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典型地震波信号各频带能量值

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频带0~100 Hz100~200 Hz200~400 Hz400~800 Hz>800 Hz
能量大小径向0.291×10-40.235×10-30.682×10-30.973×10-32.351×10-3
纵向0.527×10-50.314×10-40.414×10-41.863×10-44.418×10-4
垂向0.536×10-50.367×10-40.549×10-41.926×10-45.156×10-4
各频带能量汇总3.973×10-53.031×10-47.783×10-41.288×10-33.308×10-3
占总能量比率0.695%5.302%13.613%22.529%57.861%
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基于CEEMDAN-INHT的地下洞室爆破振动时频分析应用研究
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孙苗 1, 2a , 吴立 2a, 2b , 杨钧凯 3
爆破 | 理论与技术探索 2024,41(1): 14-20
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爆破 | 理论与技术探索 2024, 41(1): 14-20
基于CEEMDAN-INHT的地下洞室爆破振动时频分析应用研究
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孙苗1, 2a , 吴立2a, 2b , 杨钧凯3
作者信息
  • 1.湖北国土资源职业学院 环境与工程学院,武汉 430090
  • 2a.中国地质大学(武汉) 岩土钻掘与防护教育部工程研究中心,武汉 430074
  • 2b.中国地质大学(武汉) 工程学院,武汉 430074
  • 3.武汉华中科大建筑规划设计研究院有限公司,武汉 430070
  • 孙苗(1993-),女,讲师,主要从事改进HHT算法爆破地震波信号处理,(E-mail)

    SUN Miao (1993-), female, lecturer, mainly engaged in improved HHT algorithm for processing blasting seismic wave signals, (E-mail) .

通讯作者:

吴立(1963-),男,教授、博士生导师,主要研究岩土与爆破工程,(E-mail)
Application of Time-frequency Analysis of Blasting Vibration of Underground Cavern based on CEEMDAN-INHT
Miao SUN1, 2a , Li WU2a, 2b , Jun-kai YANG3
Affiliations
  • 1.College of Environment and Engineering, Hubei Land Resources Vocational College, Wuhan 430090, China
  • 2a.Engineering Research Center of Rock-Soil Drilling & Excavation and Protection, Ministry of Education, China University of Geosciences, Wuhan 430074, China
  • 2b.Faculty of Engineering, China University of Geosciences, Wuhan 430074, China
  • 3.Wuhan Huazhong University of Science and Technology Architectural Planning and Design Institute Co., Ltd., Wuhan 430070, China
出版时间: 2024-03-01 doi: 10.3963/j.issn.1001-487X.2024.01.003
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爆破地震波信号采集会因监测环境、测试系统等因素导致实测信号中混有噪声,噪声的存在将导致信号希尔伯特-黄变换(Hilbert-Huang Transform,HHT)时频分析结果失真。原因有二:其一是经验模态分解(Ensemble Empirical Mode,EMD)处理含噪爆破地震波信号会得到具有模态混淆现象的固有模态函数(Intrinsic mode function,IMF)分量;其二是Hilbert变换受Bedrosian定理的约束在处理模态混淆分量时会产生负值瞬时频率,从而造成巨大的分析误差。为获得真实的爆破振动属性需对HHT进行改进,在EMD中添加自适应噪声信号得到自适应补充集合经验模态分解(Complete Ensemble Empirical Mode Decomposition with A-daptive Noise,CEEMDAN)算法;再对CEEMDAN得到的IMF进行归一化Hilbert变换,得到改进归一化Hilbert变换(Improved Normalized Hilbert Transform,INHT)。通过上述两步可建立CEEMDAN-INHT时频分析算法,为验证该算法可有效提高含噪爆破地震波振动信号时频分析精度,进行HHT和CEEMDAN-INHT含噪仿真振动信号时频分析对比研究。最后将CEEMDAN-INHT用于某地下洞室爆破地震波信号时频分析中,发现该算法能有效克服EMD固有的模态混淆现象,同时得到反映真实爆破振动属性的时-频-能特征参数,对从频率-能量的角度进行洞室爆破开挖共振分析,实现爆破地震波危害控制具有一定的现实意义。

爆破地震波信号  /  经验模态分解  /  Hilbert变换  /  固有模态函数

The seismic wave signal acquisition will result in the mixed noise in the measured signal due to the monitoring environment, test system and other factors, and the existence of noise will lead to the distortion of the time-frequency analysis results of the signal Hilbert-Huang Transform. There are two reasons. One is that the empirical mode decomposition (EMD) algorithm will obtain the intrinsic mode function (IMF) component with modal confusion phenomenon when processing the blasting seismic wave signal containing noise; The other reason is that because the Hilbert transform is constrained by the Bedrosian theorem, which will produce negative instantaneous frequencies when dealing with modal confusion components. These lead to huge analytical errors. In order to obtain real blasting vibration properties, HHT should be improved. Complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) can be obtained by adding adaptive noise signal to EMD. Then normalized Hilbert transform is performed on the IMF obtained by CEEMDAN, and an improved normalized Hilbert transform (INHT) is obtained. Through the above two steps, the CEEMDAN-INHT time-frequency analysis algorithm can be established. In order to verify that the algorithm can effectively improve the time-frequency analysis accuracy of the noise-containing blasting seismic wave vibration signal, a comparative study on the time-frequency analysis of the HHT and CEEMDAN-INHT noise-containing simulated vibration signals is carried out. Finally, CEEMDAN-INHT is used in the time-frequency analysis of blasting seismic wave signals in an underground cavern, and it is found that the algorithm can effectively overcome the inherent mode confusion of EMD, and at the same time obtain the time-frequency-energy characteristic parameters reflecting the real blasting vibration attributes. It is of practical significance to carry out resonance analysis of blasting excavation in caverns from the perspective of frequency and energy, and to realize blasting seismic wave hazard control.

blasting seismic wave signal  /  empirical mode decomposition  /  hilbert transform  /  intrinsic mode function
孙苗, 吴立, 杨钧凯. 基于CEEMDAN-INHT的地下洞室爆破振动时频分析应用研究. 爆破, 2024 , 41 (1) : 14 -20 . DOI: 10.3963/j.issn.1001-487X.2024.01.003
Miao SUN, Li WU, Jun-kai YANG. Application of Time-frequency Analysis of Blasting Vibration of Underground Cavern based on CEEMDAN-INHT[J]. Blasting, 2024 , 41 (1) : 14 -20 . DOI: 10.3963/j.issn.1001-487X.2024.01.003
目前爆破地震波研究领域普遍采用控制爆破峰值振动速度作为控制爆破危害的依据,但除振动速度以外,爆破振动持续时间、爆破振动频率、爆破振动释放能量[1,2],爆源信息以及被保护建(构)筑物结构类型等因素也会对被保护建(构)筑物危害控制产生不可忽略的影响[3,4]
希尔伯特-黄变换(Hilbert-Huang Transform,HHT)[5]是目前应用最广泛的爆破地震波信号时频分析工具,其能建立爆破地震波信号时间-频率-能量之间的对应关系,为爆破振动控制提供分析依据。但由于爆破地震波监测信号多为含噪信号,噪声的混入使得经验模态分解(Ensemble Empirical Mode,EMD)[6]产生严重的模态混淆[7-10],而Hilbert变换处理此类分量会得到负值瞬时频率,从而导致实测爆破地震波信号的时频特征难以识别[11-14]
鉴于此对EMD进行改进得到自适应补充集合经验模态分解(Complete Ensemble Empirical Mode Decomposition with Adaptive Noise,CEEMDAN)[15]用于抑制由噪声引起的EMD模态混淆现象,再对CEEMDAN得到IMF进行改进归一化Hilbert变换(Improved Normalized Hilbert Transform,INHT)[12,16],解除Bedrosian定理的约束。最终建立了CEEMDAN-INHT时频分析模型,首先通过混有噪声的仿真信号验证该算法不仅可有效抑制EMD固有的模态混淆现象,同时得到具有实际物理意义的瞬时频率。再将该算法用于某洞室爆破地震波信号时频分析中,发现该算法可有效提取爆破地震波信号时频特征参数,实现爆破地震波危害识别,对爆破地震波危害控制具有一定的指导作用。
CEEMDAN在分解的每个阶段添加有限次的自适应白噪声[17-19],能实现在较少的平均次数下,重构误差几乎为零。具体步骤如下:
第一步:在待分析信号St)中添加自适应性白噪声Bit),i表示添加噪声次数,本文取50次。则第i次的信号可表示为St)=St)+αiBit)(i=1,2,3,…,50),其中αi为第i次添加白噪声的标准差,CEEMDAN一阶分量见式(1)。
第二步:构造新的待分解信号St)=St)+ αiBit),得到IMF2
第三步:重复“第一步”和“第二步”,直到程序终止,共产生了c个IMF,最终余项见式(2)。
对传Hilbert变换进行改进归一化处理[12,16],具体操作如下。
第一步:对CEEMDAN得到的IMF取绝对值,找出|IMFi|中的所有极大值。
第二步:求极大值点的样条包络线,记作xt)。
第三步:归一化处理,记中的所有极大值点的样条包络为x1t),计算f1t)=IMF1/x1t)。
第四步:若所有的满足,则停止。反之对IMF1重新赋值,即IMF1=f1t),重复“第二步”,得到中的所有极大值点的样条包络线为x2t),重复“第三步”得到f2t)=f1t/x2t),检验是否满足,详见式(3),其中j-1为重复的次数,一般运行2~3次即可满足需求。
式(3)中,fjt)的为IMF1的调频部分,其调幅部分wjt)可用式(4)表示。
因此归一化的IMF1可用式(5)表示,不难发现归一化本质是将IMF的调频和调幅分量分离。
第五步:对IMF1的调频部分fjt)进行Hilbert变换,见式(6)。
上述操作可实现INHT。对式(6)得到的时频谱对时间求积分得到信号的边际谱[5,6],式(7)为边际谱计算式。边际谱是每个频率在全局上的幅度,代表统计意义上的全部累加幅度。
对式(7)中的Hω)平方后,再对频率进行积分,可得到Hilbert瞬时能量[5,6],见式(8)。
构建仿真信号为混有白噪声的信号,仿真信号St)=x1t)+x2t),x1t)=wgn(1,N,0.1),即功率为0.1的噪声信号,如图1所示;x2t)=sin(2×pi×75×t),即频率为75 Hz的正弦信号,如图2所示;仿真信号如图3所示。采样点数N=1024,采样时间t=1/N∶1/N∶1。
为验证CEEMDAN-INHT算法含噪爆破地震波信号时频分析的准确性,进行EMD-HT和CEEMDAN-INHT仿真爆破振动信号时频分析,得到的变换结果即时频谱分别见图4图5
图4为EMD-HT时频谱,可发现时频谱出现了75 Hz以上的虚假分量,该分量较发散,难以识别,时频谱在时间和频率这两个维度的分辨率都不高。图5为CEEMDAN-INHT得到的时频谱图,该时频谱在时间和频率维度均具有较高分辨率,未见高频或低频模态混淆。说明CEEMDAN得到的IMF经过INHT能够得到具有实际物理意义的时频信息,即CEEMDANINHT时频分析算法不仅可有效抑制噪声信号引起的EMD模态混淆,同时得到时频分辨率双高的信号频谱图。
以烟台某地下洞室爆破开挖工程为背景,该工程为地下水封LPG洞室爆破开挖工程,包含3条主洞室,3条主洞室沿着东西向并排布置,主洞室间通过支洞室相通。工程场地较平坦,库容埋深123~127 m,库容净距仅36 m。由于围岩夹持力强,开挖爆破干扰大,施工中会出现安全问题。
由于实际爆破施工时主洞室之间库容净距仅36 m,邻近洞室爆破开挖对既有洞室的影响需要重点关注。为分析洞室开挖爆破时频特征,研究邻近洞室爆破相互作用以及爆破地震波能量特性。选用TC-4850智能爆破测振仪进行现场监测,一共布置了图6中所示的9个监测点。选取中间主洞室监测点中一条典型爆破振动信号作为研究对象,研究中间主洞室爆破开挖是否会引起已经开挖形成的北部以及南部主洞室共振。现场得到的实测典型爆破地震波监测信号三个方向分量信号如图7~图9所示。
观察图7~图9可发现本次爆破地震波监测信号采样区间为0~1.9 s,共包括9601个采样点。
图7中的径向地震波信号进行CEEMDAN,得到6个IMF和一个余项R,详见图10。从图10可知,CEEMDAN得到的IMF从高频到低频依次排列,每个IMF分量都比较稳定。其中IMF1~IMF4是本次分解的中高频分量,也是爆破地震波能量的聚集分量,爆破危害也蕴含在这些分量中,在进行爆破振动分析时,应该重点关注IMF1~IMF4所蕴含的时间-频率-能量关系;IMF5~IMF6是本次分解的低频分量,所蕴含的能量也很小,是分解的次要分量;R是余项也是趋势项,在进行NHT时,不考虑余项分量R
为突出CEEMDAN算法得到的IMF物理意义更明晰,且其分解结果能有效控制EMD模态混淆,特对图7径向地震波信号进行EMD,得到图11所示结果。可发现,IMF1高频、低幅值、低能量具有噪声信号的典型特征,可将其归为未能除去在监测中混入的噪声;IMF2~IMF5是重点频带,其中IMF3在1200 ms附近出现了中高频模态混淆,IMF4在300 ms附近有向低频发展的趋势,IMF5相对稳定;IMF6IMF7是低频分量,占有的能量比较低,IMF6在400~500 ms附近有向低频发展的趋势,IMF7相对稳定。
对比图10图11可得下列结论,CEEMDAN对噪声引起的模态混淆具有很好的抑制作用,可提高IMF的分解精度,得到物理意义更清晰的IMF。该分析结果和仿真爆破振动信号时频分析结果一致。
进一步分析,对图10得到的IMF进行INHT,再计算单个IMF边际谱,得到如图12所示单个IMF的边际谱。
图12中纵坐标ESD(Energy spectral density),指的能量谱密度。从图12可以发现爆破能量主要集中在IMF1~IMF4,即集中在频率在100 Hz以上的频段。从IMF4IMF5可以发现其纵坐标幅值能量谱密度数量级降低了1000倍,说明了低频占有的能量十分少,其占总能量的比例也十分小。
研究表明地下洞室自振频率在10~40 Hz左右[20],中间主洞室爆破开挖是否会引起北部以及南部主洞室共振,需要重点关注爆破地震波在0~100 Hz的能量分布情况。为便于定量描述各频段携带能量的大小,设置>800 Hz、400~800 Hz、200~400 Hz、100~200 Hz、0~100 Hz共5个频段,分别在这5个频带范围内对频率进行积分,并将计算结果列于表1中。
同理,图8图9中纵向、垂向地震波信号各频段瞬时能量占比也可以通过相同的方法得出,计算结果也列于表1中。
观察表1可发现,地下洞室爆破三个方向的地震波监测信号呈现出明显的能量规律,径向地震波信号能量最大,垂向地震波信号次之,纵向地震波信号最小。同时表1展示了中间主洞室爆破地震波监测信号三个方向分信号各频带能量占比,为了方便统计,对纵向、垂向地震波信号采取和径向地震波信号一致的频段划分。
通过表1以发现本次爆破地震波监测信号主要能量都集中在100 Hz以上,该结果和边际谱得到的结果一致。其中大于800 Hz所占能量比例最大,占总能量的57.861%;其次是在400~800 Hz频段,该频段能量占总能量的比例为22.529%;100 Hz以下的能量占比很小仅占总能量的0.695%。而地下洞室自振频率在10~40 Hz左右,根据表1可知该频段能量占比极低,可初步判断中间主洞室爆破开挖不会引起邻近洞室的共振。
综上所述,该工程主洞室测得的爆破地震波监测信号不会引起北部以及南部主洞室共振,因此在做地震波安全评估时,可以不考虑频率对既有洞室的影响,或者将此项作为次重点项考虑。不难发现CEEMDAN-NHT算法可进行爆破地震波信号时频分析,得到的IMF具有清晰的模态分布;进一步对CEEMDAN得到的IMF进行NHT可得到具有实际物理意义的时频能量参数,实现从频率-能量角度进行地下洞室爆破是否引起邻近既有洞室共振判断分析,有助于爆破地震波危害分析。
(1)CEEMDAN-INHT时频分析算法将CEEMDAN对噪声的抑制能力和INHT对调频分量的处理能力相结合,通过仿真爆破振动信号和实测信号时频分析检验该算法在提高爆破地震波信号时频分析精度方面具有很好的效果。
(2)CEEMDAN-INHT时频分析算法,可清晰展示爆破地震波信号所蕴含的时间-频率-能量三者之间的对应关系,该对应关系对识别爆破振动特征、判断爆破是否引发既有洞室共振具有重要的研究价值。
(3)洞室爆破能量分布和频率变化具有一定的对应性,主要能量集中在100 Hz以上频段,高频能量占比高于低频能量占比。本爆破工程具体能量分布情况是800 Hz以上所占能量比例最大,占总能量的57.861%;其次是400~800 Hz频段,占总能量的22.529%;100 Hz以下的能量占比很小仅占总能量的0.695%。
  • 国家自然科学基金(41672260)
  • 岩土钻掘与教育部工程研究中心(202215)
  • 湖北省教育厅科学研究计划指导性项目(B2022602)
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2024年第41卷第1期
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doi: 10.3963/j.issn.1001-487X.2024.01.003
  • 接收时间:2022-06-29
  • 首发时间:2026-03-20
  • 出版时间:2024-03-01
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  • 收稿日期:2022-06-29
基金
National Natural Science Foundation of China(41672260)
国家自然科学基金(41672260)
Engineering Research Center of Rock-Soil Drilling & Excavation and Protection, Ministry of Education(202215)
岩土钻掘与教育部工程研究中心(202215)
Hubei Provincial Department of Education Science Research Program Guidance Project(B2022602)
湖北省教育厅科学研究计划指导性项目(B2022602)
作者信息
    1.湖北国土资源职业学院 环境与工程学院,武汉 430090
    2a.中国地质大学(武汉) 岩土钻掘与防护教育部工程研究中心,武汉 430074
    2b.中国地质大学(武汉) 工程学院,武汉 430074
    3.武汉华中科大建筑规划设计研究院有限公司,武汉 430070

通讯作者:

吴立(1963-),男,教授、博士生导师,主要研究岩土与爆破工程,(E-mail)
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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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