Article(id=1244316348050944379, tenantId=1146029695717560320, journalId=1244215477623373855, issueId=1244316342938087728, articleNumber=null, orderNo=null, doi=10.16285/j.rsm.2024.1541, pmid=null, cstr=32223.14.j.rsm.2024.1541, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1734278400000, receivedDateStr=2024-12-16, revisedDate=null, revisedDateStr=null, acceptedDate=1743609600000, acceptedDateStr=2025-04-03, onlineDate=1774597735655, onlineDateStr=2026-03-27, pubDate=1763049600000, pubDateStr=2025-11-14, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1774597735655, onlineIssueDateStr=2026-03-27, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1774597735655, creator=13701087609, updateTime=1774597735655, updator=13701087609, issue=Issue{id=1244316342938087728, tenantId=1146029695717560320, journalId=1244215477623373855, year='2025', volume='46', issue='11', pageStart='3329', pageEnd='3672', issueExtLink='null', onlineDate='null', pubDate='null', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=1, specialIssue=null, createTime=1774597734436, creator=13701087609, updateTime=1774597825220, updator=13701087609, preIssue=null, nextIssue=null, ext={EN=IssueExt(id=1244316723801862468, tenantId=1146029695717560320, journalId=1244215477623373855, issueId=1244316342938087728, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1244316723806056773, tenantId=1146029695717560320, journalId=1244215477623373855, issueId=1244316342938087728, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null}, startPage=3355, endPage=3370, ext={EN=ArticleExt(id=1244316349195989418, articleId=1244316348050944379, tenantId=1146029695717560320, journalId=1244215477623373855, language=EN, title=Characterization of charge sensing signals during slip destabilization of faults with different roughness rock interfaces, columnId=1244316343936332083, journalTitle=Rock and Soil Mechanics, columnName=Fundamental Theory and Experimental Research, runingTitle=null, highlight=null, articleAbstract=

In order to investigate the influence of rock interface roughness on the characteristics of the charge induction signal during fault slip, the time-frequency characteristics of the multi-channel charge induction signal waveforms, the cumulative velocity of charge, the fractal dimension, and the primary and secondary frequency zones of the rock assemblage structure with different roughness during the slip process in the double-sided shear test under different vertical loads were investigated. The results show that: (1) The localized micro-rupture nucleation in the elastic deformation stage leads to multiple charge induction clusters with maximum values, which increase with the increase of interface roughness and vertical load, and then become dense and small-amplitude signals when entering into the start-slip stage. (2) With the increase of interface roughness and vertical load, the fluctuation of the accumulated charge velocity and fractal dimension are more obvious and highly correlated with the change of the waveform of the charge induction signal. In the elastic deformation stage, the accumulated charge velocity shows “slow increase in the main body and sudden increase in multiple points”, and each charge induction cluster is accompanied by the phenomenon of “first ascending and then descending” of the fractal dimension, with the main frequency area located in the low-frequency domain and the sub-main frequency area located in the high-frequency domain. In the start-slip stage, the accumulated charge velocity changes to an overall rapid increase and the fractal dimension fluctuates more obviously with the increase of fault interface roughness and vertical loading. During the start-slip stage, the charge accumulation rate changes to an overall rapid increase, and the fractal dimension is continuously downgraded, and the primary and secondary frequency regions show the phenomenon of “translational interchange”, with the primary frequency region shifted right to the high-frequency domain, and the secondary frequency region shifted left to the low-frequency domain, and the primary frequency of the charge signals at each slip stage falls into the frequency aliasing domain common to the whole process of slipping. (3) Comparing the time-frequency resolution and time-frequency focusing of the three time-frequency transform methods, wavelet transform, short-time Fourier transform and S transform, it is found that the wavelet transform performs the best in the low-frequency domain, the short-time Fourier transform the second, and the S transform the worst, while in the high-frequency domain, the S transform performs the best, the wavelet transform the second, and the short-time Fourier transform the worst. (4) Differences in charge signals of sensors at different locations during fault slip destabilization are mainly related to the aggregation of charges in specific regions caused by locally concentrated micro-ruptures before the start-slip phase, and are mainly caused by the change of misalignment of the relative positions between the slip surface and the sensors after the start-slip phase.

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为探究岩石界面粗糙度对断层滑移过程电荷感应信号特征的影响,研究了不同粗糙度岩石组合结构在不同竖向荷载下双面剪切试验滑移全过程多通道电荷感应信号波形、电荷累计速度、分形维数和主频区-次主频区指标的时频特征。研究结果表明:(1)弹性变形阶段断层面出现的局部微破裂成核导致电荷感应信号波形表现为多次电荷感应簇并出现最大值,这种电荷感应簇随着界面粗糙度和竖向荷载的提高而增多,进入启滑阶段则变为密集的小幅信号。(2)随断层界面粗糙度和竖向荷载增加,电荷累计速度和分形维数波动更为明显,且与电荷感应信号波形变化高度关联。弹性变形阶段电荷累计速度表现为“主体慢增,多点突增”,每次电荷感应簇都伴随着分形维数的“先升维,后降维”现象,主频区位于低频域,次主频区位于高频域;启滑阶段电荷累计速度转变为全面快速增加,分形维数整体不断降维,主频区和次主频区表现出“平移互换”现象,主频区右移至高频域,次主频区则左移至低频域,且各滑移阶段电荷信号主频均落于滑移全过程共有频率混叠域内。(3)对比小波变换、短时傅里叶变换和S变换3种时频变换方法在滑移失稳前的时频分辨率与时频聚焦性发现,在低频域,小波变换表现最好,短时傅里叶变换次之,S变换最差,而在高频域,S变换表现最好,小波变换次之,短时傅里叶变换最差。(4)断层滑移失稳过程中不同位置传感器电荷信号的差异在启滑阶段前主要与局部集中微破裂引起的电荷特定区域聚集有关,在启滑阶段后则主要由滑移面与传感器之间相对位置的错动变化引起。

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赵扬锋,男,1979年生,博士,教授,博士生导师,主要从事矿山灾害力学的研究。E-mail:

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赵扬锋,男,1979年生,博士,教授,博士生导师,主要从事矿山灾害力学的研究。E-mail:

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figureFileSmall=JHgXjqYK9rETmOQQnSppLQ==, figureFileBig=zBmps7YsFFdcjNQ4tXF6aQ==, tableContent=null), ArticleFig(id=1244316371186725247, tenantId=1146029695717560320, journalId=1244215477623373855, articleId=1244316348050944379, language=EN, label=Fig.18, caption=Charge induction signal multi-indicator precursor early warning system, figureFileSmall=1qRFx4W+8tXrO+9rFYLZbg==, figureFileBig=L9SkdrTG+s89fzhoi/SPtw==, tableContent=null), ArticleFig(id=1244316371341914507, tenantId=1146029695717560320, journalId=1244215477623373855, articleId=1244316348050944379, language=CN, label=图18, caption=电荷感应信号多指标前兆预警系统, figureFileSmall=1qRFx4W+8tXrO+9rFYLZbg==, figureFileBig=L9SkdrTG+s89fzhoi/SPtw==, tableContent=null), ArticleFig(id=1244316371560018323, tenantId=1146029695717560320, journalId=1244215477623373855, articleId=1244316348050944379, language=EN, label=Table 1, caption=

Classification of red sandstone

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JRC组合试件编号加载速度/(kN·s−1竖向荷载/kN
17.19A0.850
17.91B10.450
B20.825
B30.850
19.98C10.450
C20.825
C30.850
), ArticleFig(id=1244316371698430363, tenantId=1146029695717560320, journalId=1244215477623373855, articleId=1244316348050944379, language=CN, label=表1, caption=

红砂岩试样分组

, figureFileSmall=null, figureFileBig=null, tableContent=
JRC组合试件编号加载速度/(kN·s−1竖向荷载/kN
17.19A0.850
17.91B10.450
B20.825
B30.850
19.98C10.450
C20.825
C30.850
), ArticleFig(id=1244316371929117092, tenantId=1146029695717560320, journalId=1244215477623373855, articleId=1244316348050944379, language=EN, label=Table 2, caption=

Peak time and peak of charge pulse clusters in each channel during the sliding elastic deformation stage for groups A and C3

, figureFileSmall=null, figureFileBig=null, tableContent=
AC3
1通道2通道3通道1通道2通道3通道
到达时间/s峰值/pC到达时间/s峰值/pC到达时间/s峰值/pC到达时间/s峰值/pC到达时间/s峰值/pC到达时间/s峰值/pC
30.810 297−2.0330.813 50−30.5230.316 86−7.6431.619 590.4531.619 590.5431.388 88−0.52
43.392 0303.4943.398 59−6.8142.909 773.3636.541 061.7336.541 062.1336.541 30−3.01
50.144 9302.7050.184 89−9.0849.689 213.9143.916 150.5243.924 962.1344.007 433.43
58.717 9103.8058.764 62−9.2258.219 60−6.4948.551 720.2348.541 060.2648.593 091.89
61.458 0903.4064.494 80−9.4763.957 61−6.7155.626 020.5855.626 020.7355.626 021.34
68.639 8204.4868.658 85−12.9468.140 79−6.5460.765 561.7260.765 562.30
73.786 4306.6773.825 4411.7973.288 046.8166.495 630.1765.580 770.4866.565 121.10
74.062 720.7473.390 30−1.98
), ArticleFig(id=1244316372059140521, tenantId=1146029695717560320, journalId=1244215477623373855, articleId=1244316348050944379, language=CN, label=表2, caption=

A和C3组滑移弹性变形阶段各通道电荷脉冲簇峰值时间与峰值

, figureFileSmall=null, figureFileBig=null, tableContent=
AC3
1通道2通道3通道1通道2通道3通道
到达时间/s峰值/pC到达时间/s峰值/pC到达时间/s峰值/pC到达时间/s峰值/pC到达时间/s峰值/pC到达时间/s峰值/pC
30.810 297−2.0330.813 50−30.5230.316 86−7.6431.619 590.4531.619 590.5431.388 88−0.52
43.392 0303.4943.398 59−6.8142.909 773.3636.541 061.7336.541 062.1336.541 30−3.01
50.144 9302.7050.184 89−9.0849.689 213.9143.916 150.5243.924 962.1344.007 433.43
58.717 9103.8058.764 62−9.2258.219 60−6.4948.551 720.2348.541 060.2648.593 091.89
61.458 0903.4064.494 80−9.4763.957 61−6.7155.626 020.5855.626 020.7355.626 021.34
68.639 8204.4868.658 85−12.9468.140 79−6.5460.765 561.7260.765 562.30
73.786 4306.6773.825 4411.7973.288 046.8166.495 630.1765.580 770.4866.565 121.10
74.062 720.7473.390 30−1.98
), ArticleFig(id=1244316372205941175, tenantId=1146029695717560320, journalId=1244215477623373855, articleId=1244316348050944379, language=EN, label=Table 3, caption=

Peak time and peak of charge pulse clusters in each channel during the sliding elastic-plastic deformation stage for groups A and C3

, figureFileSmall=null, figureFileBig=null, tableContent=
AC3
1通道2通道3通道1通道2通道3通道
到达时间/s峰值/pC到达时间/s峰值/pC到达时间/s峰值/pC到达时间/s峰值/pC到达时间/s峰值/pC到达时间/s峰值/pC
113.284 160.41117.651 10−0.87117.651 103−1.31117.731 733.07
119.605 74−0.44119.017 064.36120.121 431.51120.120 8802.71120.072 13−2.96
121.128 210.56121.007 013.03
), ArticleFig(id=1244316373787193789, tenantId=1146029695717560320, journalId=1244215477623373855, articleId=1244316348050944379, language=CN, label=表3, caption=

A和C3组试验滑移弹塑性变形阶段各通道电荷脉冲簇峰值时间与峰值

, figureFileSmall=null, figureFileBig=null, tableContent=
AC3
1通道2通道3通道1通道2通道3通道
到达时间/s峰值/pC到达时间/s峰值/pC到达时间/s峰值/pC到达时间/s峰值/pC到达时间/s峰值/pC到达时间/s峰值/pC
113.284 160.41117.651 10−0.87117.651 103−1.31117.731 733.07
119.605 74−0.44119.017 064.36120.121 431.51120.120 8802.71120.072 13−2.96
121.128 210.56121.007 013.03
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不同粗糙度岩石界面断层滑移失稳过程电荷感应信号特征分析
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赵扬锋 1 , 龚政 1 , 王凯兴 1 , 司绪 1 , 刘玉春 1, 2 , 张丽丽 2 , 梁钦锋 1
岩土力学 | 基础理论与实验研究 2025,46(11): 3355-3370
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岩土力学 | 基础理论与实验研究 2025, 46(11): 3355-3370
不同粗糙度岩石界面断层滑移失稳过程电荷感应信号特征分析
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赵扬锋1 , 龚政1, 王凯兴1, 司绪1, 刘玉春1, 2, 张丽丽2, 梁钦锋1
作者信息
  • 1.辽宁工程技术大学 力学与工程学院,辽宁 阜新 123000
  • 2.辽宁工程技术大学 理学院,辽宁 阜新 123000
  • 赵扬锋,男,1979年生,博士,教授,博士生导师,主要从事矿山灾害力学的研究。E-mail:

Characterization of charge sensing signals during slip destabilization of faults with different roughness rock interfaces
Yang-feng ZHAO1 , Zheng GONG1, Kai-xing WANG1, Xu SI1, Yu-chun LIU1, 2, Li-li ZHANG2, Qin-feng LIANG1
Affiliations
  • 1.School of Mechanics and Engineering, Liaoning Technical University, Fuxin, Liaoning 123000, China
  • 2.College of Science, Liaoning Technical University, Fuxin, Liaoning 123000, China
出版时间: 2025-11-14 doi: 10.16285/j.rsm.2024.1541
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为探究岩石界面粗糙度对断层滑移过程电荷感应信号特征的影响,研究了不同粗糙度岩石组合结构在不同竖向荷载下双面剪切试验滑移全过程多通道电荷感应信号波形、电荷累计速度、分形维数和主频区-次主频区指标的时频特征。研究结果表明:(1)弹性变形阶段断层面出现的局部微破裂成核导致电荷感应信号波形表现为多次电荷感应簇并出现最大值,这种电荷感应簇随着界面粗糙度和竖向荷载的提高而增多,进入启滑阶段则变为密集的小幅信号。(2)随断层界面粗糙度和竖向荷载增加,电荷累计速度和分形维数波动更为明显,且与电荷感应信号波形变化高度关联。弹性变形阶段电荷累计速度表现为“主体慢增,多点突增”,每次电荷感应簇都伴随着分形维数的“先升维,后降维”现象,主频区位于低频域,次主频区位于高频域;启滑阶段电荷累计速度转变为全面快速增加,分形维数整体不断降维,主频区和次主频区表现出“平移互换”现象,主频区右移至高频域,次主频区则左移至低频域,且各滑移阶段电荷信号主频均落于滑移全过程共有频率混叠域内。(3)对比小波变换、短时傅里叶变换和S变换3种时频变换方法在滑移失稳前的时频分辨率与时频聚焦性发现,在低频域,小波变换表现最好,短时傅里叶变换次之,S变换最差,而在高频域,S变换表现最好,小波变换次之,短时傅里叶变换最差。(4)断层滑移失稳过程中不同位置传感器电荷信号的差异在启滑阶段前主要与局部集中微破裂引起的电荷特定区域聚集有关,在启滑阶段后则主要由滑移面与传感器之间相对位置的错动变化引起。

断层滑移  /  粗糙度  /  电荷感应  /  时频域分析  /  前兆预警

In order to investigate the influence of rock interface roughness on the characteristics of the charge induction signal during fault slip, the time-frequency characteristics of the multi-channel charge induction signal waveforms, the cumulative velocity of charge, the fractal dimension, and the primary and secondary frequency zones of the rock assemblage structure with different roughness during the slip process in the double-sided shear test under different vertical loads were investigated. The results show that: (1) The localized micro-rupture nucleation in the elastic deformation stage leads to multiple charge induction clusters with maximum values, which increase with the increase of interface roughness and vertical load, and then become dense and small-amplitude signals when entering into the start-slip stage. (2) With the increase of interface roughness and vertical load, the fluctuation of the accumulated charge velocity and fractal dimension are more obvious and highly correlated with the change of the waveform of the charge induction signal. In the elastic deformation stage, the accumulated charge velocity shows “slow increase in the main body and sudden increase in multiple points”, and each charge induction cluster is accompanied by the phenomenon of “first ascending and then descending” of the fractal dimension, with the main frequency area located in the low-frequency domain and the sub-main frequency area located in the high-frequency domain. In the start-slip stage, the accumulated charge velocity changes to an overall rapid increase and the fractal dimension fluctuates more obviously with the increase of fault interface roughness and vertical loading. During the start-slip stage, the charge accumulation rate changes to an overall rapid increase, and the fractal dimension is continuously downgraded, and the primary and secondary frequency regions show the phenomenon of “translational interchange”, with the primary frequency region shifted right to the high-frequency domain, and the secondary frequency region shifted left to the low-frequency domain, and the primary frequency of the charge signals at each slip stage falls into the frequency aliasing domain common to the whole process of slipping. (3) Comparing the time-frequency resolution and time-frequency focusing of the three time-frequency transform methods, wavelet transform, short-time Fourier transform and S transform, it is found that the wavelet transform performs the best in the low-frequency domain, the short-time Fourier transform the second, and the S transform the worst, while in the high-frequency domain, the S transform performs the best, the wavelet transform the second, and the short-time Fourier transform the worst. (4) Differences in charge signals of sensors at different locations during fault slip destabilization are mainly related to the aggregation of charges in specific regions caused by locally concentrated micro-ruptures before the start-slip phase, and are mainly caused by the change of misalignment of the relative positions between the slip surface and the sensors after the start-slip phase.

fault slip  /  roughness  /  charge induction  /  time-frequency domain analysis  /  precursor warning
赵扬锋, 龚政, 王凯兴, 司绪, 刘玉春, 张丽丽, 梁钦锋. 不同粗糙度岩石界面断层滑移失稳过程电荷感应信号特征分析. 岩土力学, 2025 , 46 (11) : 3355 -3370 . DOI: 10.16285/j.rsm.2024.1541
Yang-feng ZHAO, Zheng GONG, Kai-xing WANG, Xu SI, Yu-chun LIU, Li-li ZHANG, Qin-feng LIANG. Characterization of charge sensing signals during slip destabilization of faults with different roughness rock interfaces[J]. Rock and Soil Mechanics, 2025 , 46 (11) : 3355 -3370 . DOI: 10.16285/j.rsm.2024.1541
随着我国煤矿逐渐进入深部开采,开采过程中受断层冲击地压的影响也日益加剧,冲击地压预警与防治已成为煤矿安全生产领域亟待解决的关键问题[1]。预计未来十几年我国有1/3的煤矿矿井将增加1 km以上挖掘深度[2]。断层作为深部开采中最可能诱发动力灾害的地质条件之一,近2/3的冲击地压事故是断层等地质构造引发的断层滑移型冲击地压[3]。因此,研究断层在不同条件下发生滑移时的力学特征与前兆预警方法,对深部开采中预防断层滑移型灾害具有重要实际意义。
前人主要通过剪切试验来研究断层滑移特性[4],国内外学者已经利用断层剪切试验对断层滑移的机制和特征进行了大量研究。Brace等[5]通过对含有预制断层的岩样进行剪切摩擦试验,观察到荷载呈现出长期积累与瞬间释放的交替循环。刘玉春等[6]利用声发射与电荷感应监测系统对花岗岩试件开展双轴加载试验,研究了不同断层倾角和加载速率对断层黏滑特性的影响。宋义敏等[7-8]开展岩石的双面剪切试验,发现随着岩石表面位移场的演化,裂纹尖端会阻碍位移传递,形成压应变集中区,得出变形能密度与滑动面滑动速度演化及规律。缪阿丽等[9]利用三轴摩擦试验研究了含水盐岩断层带摩擦滑动过程中的声发射特征,认为黏滑和稳滑的声发射特征差异与其变形主导机制的不同相关。粗糙度作为影响断层结构面剪切滑移的重要力学特性之一,在一定程度上控制着断层的滑移和失稳等行为[10]。矿震的发生取决于裂隙的滑动稳定性[11],因此,研究断层面粗糙度对断层滑移失稳特征的影响具有重要意义。Barton[12]在1973年首次提出不同粗糙度岩体结构面的强度模型,并引入结构面粗糙度系数JRC(joint roughness coefficient)的概念。李利萍等[13-14]利用煤岩界面超低摩擦试验装置研究了煤岩组合结构在不同界面粗糙度下的发生滑移时的超低摩擦特征,发现粗糙度越小,煤岩组合结构越容易发生超低摩擦现象。Liu等[15-16]认为沿剪切方向的最大节理粗糙系数值能够较好地表征总节理面以及估算其抗剪强度。范祥等[17]开展了双结构面类岩试样的剪切试验,建立了综合考虑JRC双结构面峰值剪切强度影响的经验公式。
众多国内外学者研究表明,岩石变形破裂过程会产生电荷感应信号,岩石摩擦滑动中也会伴随产生电荷感应信号,通过分析岩石摩擦滑动过程电荷信号特征能够深入了解岩石滑移失稳的力学特征。赵扬锋等[18-20]利用剪切摩擦试验对不同预制倾角断层失稳过程的声-电特征进行分析,发现试样在弹性变形阶段和失稳阶段都会产生明显的电荷感应同步前兆信号,得到了不同侧压和断层倾角下断层黏滑过程中声发射信号和电荷感应信号的能量、分形维数、频谱幅值等多源参量联合演化规律。Leeman等[21]研究发现,断层剪切滑移在初始加载的黏滞期间长期充电,进入滑移后开始放电。Daniels等[22]认为滑移时产生的电荷信号与断层接触面材料的表面颗粒特性有关,而不是与断层材料有关。王恒[23]、王仲强[24]等研究了煤岩的电位信号,发现总体电位信号都呈现出多尺度多重分形特征,认为压电效应是砂岩试样的关键带电原因。
综上所述,大量学者研究了粗糙度变化对断层滑移失稳特征的影响,并利用剪切试验获得了断层滑移过程电荷感应前兆信息,但在岩石界面粗糙度对断层滑移过程电荷感应信号前兆特征的影响鲜有报道。本文利用双面剪切试验研究不同粗糙度岩石组合结构在不同竖向荷载下滑移失稳过程电荷感应信号演化特征,为深部开采中断层滑移型灾害的前兆预警提供理论和试验基础。
试验系统由试验加载与位移记录系统、粗糙度测量仪、多通道电荷感应数据采集系统和电磁屏蔽系统组成。
试验加载与位移记录系统为岩煤结构静动组合加载试验系统[25]。如图1所示,加载主体部分为静动组合加载试验机,包括压力室、轴向液压油缸、蓄能气缸和水平向液压油缸、蓄能气缸。加载系统可以实现轴向和侧向静载双向控制与位移记录,轴向和侧向加载控制范围为0~600 kN,位移记录范围为0~100 mm,载荷控制精度和载荷测量精度为5‰,位移测量精度为1 μm。试验加载速度采用慢速加载(0.4 kN/s)和快速加载(0.8 kN/s)两种加载方式。
电荷感应信号数据采集系统采用自行研制的多通道数据采集器,主要由电荷传感器、A/D数字转换器和数据采集器3个模块构成。电荷传感器的灵敏度ACQ=1×1011 V/C,所以电荷感应可测范围为±1.526×10−11~5×10−11 C,试验时选用3个电荷传感器。为确保传感器有效且明显的监测到岩石组合结构滑移失稳过程中的电荷感应信号,电荷传感器1和2布置在岩石组合结构的上摩擦面。电荷传感器3布置在岩石组合结构的下摩擦面。固定电荷传感器探头正对滑动面中心位置且距滑动面表面5 mm;电荷传感器布置如图2所示。
现场取回红砂岩加工成7组标准的岩石组合试样,每组试样由上下两块固定岩样和中部一块滑动岩样组成。试件尺寸(长×宽×高):两端岩样为250 mm×50 mm×50 mm,中间岩样为200 mm× 50 mm×100 mm。将岩样上、下摩擦面分别用理论粒径为0.423、0.169、0.016 mm的砂纸打磨,依据王来贵[26]、李利萍[13-14]等的计算方法得到不同砂纸打磨红砂岩试件的JRC分别为17.19、17.91和19.98。粗糙度系数越大,红砂岩表面越粗糙,相同目数砂纸打磨的红砂岩试件表面粗糙度系数误差为0.4%~0.9%,符合试验要求。
将组合岩样按照红砂岩试样JRC进行编号(如表1所示),编号为A、B1~B3、C1~C3。岩样加工后处于自然干燥状态备用。图3为加工后备用的部分岩样。
(1)将每组试样准确放置于加载平台中央,竖直方向和水平方向均采用钢板垫层以确保试样受力均匀。
(2)按照图2中传感器布置方式连接数据采集系统,设置采样频率,设置加载系统与数据采集系统网络时间一致,确保各系统的数据在时域准确同步。
(3)对7组试样依次进行静载作用下的双面剪切试验。加载时先将竖向静载施加至设定值,再逐步施加水平静载,直至试样开始快速滑动。试验前用铜丝网笼罩试验系统进行屏蔽,试验时先打开加载系统,等待系统稳定后再打开数据采集系统,试验结束后先关闭数据采集系统,再关闭加载系统,减少对信号采集的影响。
图4为A、B1~B3和C1~C3组岩石组合结构滑失稳的时间-水平剪应力-水平位移,将水平荷载开始施加时刻记为0。图5为岩层黏滑周期和水平剪应力峰值。
图45可知:
(1)水平荷载开始施加后,静载作用下岩石组合结构滑移失稳过程可以划分为弹性变形阶段、启滑阶段和剪切塑性变形阶段(快滑期)[27],前两个阶段可以合称为慢滑期。岩样的矿物组成等因素使断层表面存在许多凹凸体[28]。由于凹凸体的存在,断层面摩擦强度不均匀分布。凹凸体的相互作用决定了断层的宏观摩擦强度,控制着断层摩擦滑动过程[29]。慢滑期具有时间长和速度慢的特点,并伴随凹凸体大量微破裂,适合滑移失稳前兆预警。进入快滑期,断层面平均剪应力达到峰值,断层摩擦强度趋于极限,凹凸体被爬越剪断,储存的弹性能突然释放,断层失去力学平衡。此时断层累积的应力逐渐加速释放,直到断层快速错动失稳,断层剪应力突降[30]。断层面的力学平衡被打破后进入自失稳演化,岩层位移出现快速增加,当滑动位移接近50 mm行程时去除水平荷载,此时位移小幅回弹。
(2)低竖向荷载下岩层滑移形式表现为稳滑-震颤相结合,高竖向荷载下岩层滑移形式则表现为黏滑。当断层发生黏滑时,粗糙度的增加会使断层面峰值应力增加,黏滑周期缩短和黏滑事件增多。黏滑周期可以反映断层黏滑的难易程度[12],可以看出JRC的增加使断层更容易发生黏滑事件。
为探究传感器位置对电荷感应信号的影响,将布置在断层上界面的1号和2号电荷传感器与布置在断层下界面的3号电荷传感器接收到的电荷信号进行对比。
各组试件滑移过程中不同位置传感器接收到的电荷信号波形总体上具有一定的相似性,以A和C3组试件滑移为例分析。图67分别为A和C3组试件各传感器接收到的电荷感应信号波形与累计电荷量。从图67可以看出,在滑移的弹性变形阶段,3个电荷传感器都接收到丰富的大幅值电荷感应信号,并以多次电荷脉冲簇的形式出现。进入启滑阶段后,A和C3组都几乎没有出现大幅值电荷感应信号,而是以小幅值的连续信号为主。当滑移进入剪切塑性变形阶段,每次断层面应力降低前都伴随大幅值电荷脉冲簇。现有研究表明[31-32],摩擦作用和尖端微破裂引起电荷分离等因素都会引起岩体变形破坏过程中同时产生电荷信号。
由于传感器探头位置不同,断层面滑移时接收到电荷脉冲簇的峰值时间和峰值有所差异。表2为A和C3组滑移弹性变形阶段各通道电荷脉冲簇峰值时间与峰值。红砂岩试样为绝缘体,在滑移过程中会形成空穴和电子俘获中心,导致摩擦起电[33],Onuma[34]和Leeman[35]等认为,地震成核阶段出现的较大电荷信号与剪切带缓慢滑移引起的摩擦起电有关。由表2可知,A组在滑移弹性变形阶段,电荷1~3通道都接收到7次大幅值电荷脉冲簇,其中3通道峰值时间最早,各通道峰值时间差为0.496 64 s。对比不同脉冲簇到时可以发现,除第5次电荷脉冲簇为1通道峰值时间最早,为61.458 09 s,最大时间差为3.036 8 s外,其他6次电荷脉冲簇均为3通道峰值时间最早,2通道峰值时间最晚,各通道峰值时间最大差值范围为0.488 82~0.545 00 s。C3组在滑移弹性变形阶段,电荷1~3通道接收到8次大幅值电荷脉冲簇,其中3通道峰值时间最早,各通道峰值时间最大差值为0.230 71 s。第6次脉冲簇仅有2和3通道接收到电荷信号。第8次脉冲簇仅有1和3通道接收到电荷信号。7次电荷脉冲簇不同通道峰值时间最大差值范围为0~0.984 35 s。A组7次电荷脉冲簇均为2通道幅值较大,且都为负电荷,C3试验8次电荷脉冲簇中有7次均为3通道峰值较大。
通过上述分析可知,各组滑移过程中不同电荷事件最快峰值时间和峰值均较为明显地集中出现在特定位置传感器。研究表明,断层滑移失稳伴随有凹凸体的局部微破裂和相互摩擦,进而在断层面上集聚电荷[20],初步认为弹性变形阶段各通道电荷脉冲簇接收情况的差异主要与缓慢滑移阶段局部集中微破裂引起的电荷在特定区域聚集有关。
表3为A和C3组滑移剪切塑性变形阶段各通道电荷脉冲簇峰值时间与峰值。由表3可知,A组在滑移剪切塑性变形阶段接收到两次大幅值电荷脉冲簇。第1次电荷脉冲簇事件仅有1通道接收到电荷感应信号,第2次电荷簇事件1和3通道接收到电荷感应信号。C3组为在滑移剪切塑性变形阶段接收到3次电荷脉冲簇,第3次脉冲簇仅有1和3通道接收到峰值信号。3次电荷脉冲簇各通道峰值时间最大差值范围为0.080 63~0.121 20 s。对比分析A和C3组电荷簇事件可以发现,2通道在快速位移阶段均出现没有接收到电荷信号的情况。
考虑到1和2通道分别位于上断层面前部和后部,3号传感器位于下断层面中部,当滑移进入快速位移阶段时,A和C3组中部岩层已经分别产生了9.79 mm和13.71 mm的位移。滑移过程中1号传感器逐渐接近岩层中部,信号强度逐渐变大;3号传感器则逐渐远离岩层中部,信号强度逐渐变小。可以认为剪切塑性变形阶段各通道电荷脉冲簇接收情况的差异主要是由启滑后滑移面与传感器之间的相对位置错动变化引起。随着界面粗糙度增加,各阶段电荷感应簇明显增多。
图8为A、B1~B2和C3组各阶段电荷量占比分布与电荷累计速度图,其中电荷量占比为3个通道的平均电荷占比,电荷累计速度为各阶段的平均累计速度。
图8表2所示,电荷感应信号主要产生于滑移的弹性变形阶段,占总电荷信号的69%以上,但总体累计速度较慢,仅在大幅值电荷感应簇出现时突增,呈现出“主体慢增,多点突增”的特点。启滑阶段电荷累计则转变为全面快速增加。随着JRC的增加,滑移各阶段电荷累计速度均提升,其中慢滑期电荷量占比逐渐提高。C3组弹性变形阶段电荷量占比较A组提高6.319%,启滑阶段电荷量占比较A组提高5.065%,启滑阶段电荷量占比较A组降低11.424%。竖向荷载影响下的B1组黏滑和B2组稳滑也呈现出类似的规律。弹性变形阶段,由于断层面存在一些弱段和大量凹凸体,各处的摩擦强度分布并不一致。在断层面应力积累的过程中,外部荷载接近凹凸体破裂强度时,局部区域会先发生微破裂和微滑移[36],从而产生电荷信号。在竖向荷载作用下产生的压电效应和凹凸体微破裂与微滑移的共同影响下[37],凹凸体闭锁过程中出现密集的电荷脉冲簇,并累计大量电荷。JRC的提升使断层面凹凸体强度提高,竖向荷载的提升会增加凹凸体之间的闭合度,均使滑移形式从稳滑向黏滑改变,从而在凹凸体闭锁和破裂的过程中产生更多电荷脉冲簇。
综上所述,可以认为JRC与竖向荷载的变化是通过改变断层滑移的形式,进而影响滑移过程中阶段电荷量占比和电荷累计速度。高粗糙度和高竖向荷载下断层发生黏滑,弹性变形阶段和启滑阶段的电荷量占比与电荷累计速度均有明显提高,说明高强度凹凸体和高摩擦作用会加剧滑移面破裂程度,同时产生更强的电荷信号。
根据分形理论,断层滑移过程中产生的电荷感应信号具有一定的分形特征,分形维数可以较好地反映信号在特定时域内的波动程度。分形维数Dt的计算公式为[38]
式中:T为总时间;tT过程中幅值之间的时间间隔;Ct)为电荷信号幅值随时间分布的相关积分。
由式(1)可知,当电荷感应信号在某一时期波动幅度较小时,处于这一时段的分形维数会较为集中,可以表征强度较小的破裂,而当某一时段电荷信号经历大幅波动,处于这一时段的分形维数会较为离散,且波峰附近的分形维数会出现“峰前升,峰后降”的特征,可以表征强度较大的破裂。
图910分别为A和C3组试验各滑移阶段电荷感应信号幅值的时间分形维数。由图910可知,在弹性变形阶段前期,分形维数离散度较小,没有发生较大破裂事件。随着断层面凹凸体闭合,局部应力集中加剧,弹性变形阶段中后期每次大幅值电荷感应簇的出现都伴随有分形维数“峰前升,峰后降”的大幅波动。启滑阶段分形维数没有单个大幅波动,但整体表现出不断下降的趋势。A组仅在稳滑开始前时出现一次较大波动,而C3组每次黏滑开始前都有显著的大幅波动。由此可见,分形维数可以较好地反映断层面滑移各阶段特征以及能量的释放程度。
快速傅里叶变换(fast Fourier transform,简称FFT)可以直接提供信号的全局性频谱特征,对表征岩石滑移损伤具有重要意义。分别选取滑移失稳在弹性变形阶段、启滑阶段和剪切塑性变形阶段的典型电荷感应信号,利用FFT对电荷感应信号进行频域处理,得到二维频谱信息。在噪音等外界因素的影响下,试验直接获取的大量电荷感应信号会存在部分错误信息,导致对频域的统计分析易出现误差[39]
由3.1节可知,滑移在剪切塑性变形阶段会短时间内发生位移的迅速增加,不利于滑移失稳的前兆预警。由于断层滑移失稳不同阶段破裂形式的差异性,地球物理监测信号的主频区会出现左右平移现象[10],但是仅考虑主频区的演化特征并不能很好地反映滑移的阶段变化。为排除试验错误信息的干扰,迅速精准识别并自动拾取主频区和次主频区等关键信息,得到滑移阶段频域演化特征,准确反映断层滑移的阶段转换。参照王创业等[40]的分析流程,开发了一种基于Matlab软件平台的电荷感应频谱参数自动拾取程序,可以对试验过程中单个电荷脉冲簇或滑移阶段电荷感应信号进行精确去噪、频区识别、拾取主频与次主频和主频区与次主频区等频域信息。
以C3组滑移弹性变形阶段第一次电荷感应簇为例,说明从原始信号中拾取频谱参数的算法实现过程(如图11所示):①步骤为滤波,利用基于切比雪夫原理开发的带阻滤波器对原始信号进行多频柔性降噪。②步骤为FFT,用于获得降噪后电荷信号的二维频谱图,其频率和幅值数据分两列储存在M中(M为两列的变量)。③步骤为模糊化,是划分主频区和次主频区的核心步骤,将M中幅值满足Mn−1<Mn<Mn+1或同时满足Mn>Mn−1Mn< Mn+1的数据点存入M1MnMn−1Mn+1分别为M中幅值列的第n个、第n−1个和第n+1个数据,其中n>1),经过k−1次迭代,直至出现明显的频域分区,将迭代后的频率和幅值数据存入Mk中,并绘制模糊化二维频谱图如图11(d)所示。④步骤为寻峰,即拾取模糊化频谱图中最小分隔的独立峰值,经过反复测试,最小分隔值为2 Hz时寻峰效果最好,将符合拾取条件峰值的频率和幅值存入向量X中。⑤步骤为确定主频和次主频等频谱参数,将位于主频和次主频能量带范围内的频域分别作为主频区和次主频区。在图11(f)中定义以主频和次主频为中心,首次衰减至主频和次主频幅值20%以下凹点的频率为主频区和次主频区边界。
图1213分别为A和C3组滑移各阶段频谱特征。在地下工程中,冲击灾害发生前经常能够监测到明显的电荷感应信号[41]。由图1213可知,滑移第1阶段电荷信号主频区集中在低频区域,主频均为24 Hz左右,与此同时,在主频区的右侧伴随次主频区信号。随着JRC的提高,次主频区向高频移动,A组次主频为146.68 Hz,C3组次主频则右移至619.88 Hz。第2阶段主频区和次主频区表现出“平移互换”现象,主频区右移至高频区域,次主频区则左移至低频区域。滑移第3阶段频谱为单峰信号,主频区出现在低频区域。初步研究认为,主频区和次主频区演化与不同阶段滑移的主导机制有关。滑移弹性变形阶段出现大幅值突发电荷信号,对应凹凸体闭锁过程中的破裂和断层微滑移,由于断层面上的破裂并不是均一形式的平均破裂,而是在凹凸体处产生较大的破裂[42],因此主频区集中在低频区域。启滑阶段出现小幅值的密集电荷信号,对应断层面凹凸体闭锁后接近极限强度而逐渐增多的高频微破裂事件。进入剪切塑性变形阶段,随着水平荷载的进一步增加,断层摩擦强度趋于极限,断层面平均剪应力达到峰值点,凹凸体被突然剪断,释放出大幅值低频电荷信号。滑移弹性变形阶段主频区混叠域为24.79~53.4 Hz,启滑阶段主频区混叠域为496.29~670.62 Hz,滑移剪切塑性变形阶段主频区混叠域为54.17~120.08 Hz,对比不同阶段主频区混叠域和主频落点,可以发现A组和C3组各阶段电荷信号主频均落于混叠域内。
综上所述,断层滑移处于不同阶段时滑动机制的差异在微观层面影响凹凸体间力链网络的破坏进程,进而引起电荷信号主频与次主频等频域特征的改变。综合考虑启滑前后出现的主频区与次主频区“平移互换”和各滑移阶段电荷信号主频均落于滑移过程共有频率混叠域内可以有效观测滑移进程,对滑移失稳的预警有着重要意义。
断层滑移产生的电荷信号为复杂的非平稳非线性信号,FFT虽然在阶段性信号频谱分析的上有一定优势,但无法准确提供信号的瞬时频率特征。线性变换法具有计算简单、没有交叉项干扰和具备时频分辨率与时频聚焦性的特点[43],更加有利于分析单个电荷感应信号。为进一步揭示滑移不同阶段电荷信号的瞬时频率演化规律,对前兆信息的时频特征进行精确地捕捉和分析,分别采用线性变换中较为常见的短时傅里叶变换(short-time Fourier transform,简称STFT)、小波变换和S变换获取电荷信号时频谱(S变换是一种时频分辨率不变的分析方法)。STFT是一种单一分辨率的分析方法,通过滑动时窗计算频谱,其时频分辨率会受到Heisenberg测不准原理的限制。小波变换是一种窗口面积不变,时窗长度可变的时频分析法,在低频区域具有较高的时频分辨率。
图1417为A组滑移的弹性变形阶段和启滑阶段利用3种时频变换方法得到的电荷感应信号时频变换谱。由图1417可知,滑移前两阶段典型前兆信号在特定时间和频段均存在强度集中现象。对比3种时频变换方法的时频分辨率与时频聚焦性可以发现,在低频区域,小波变换表现最好,短时傅里叶变换次之,S变换最差。在高频区域,S变换表现最好,小波变换次之,短时傅里叶变换最差。在滑移前两个阶段,综合利用小波变换的低频信息和S变换的高频信息来捕捉主频区-次主频区实时变化情况,从而实时识别滑移进程,可以有效地获取滑移失稳的时频前兆特征。
通过对断层滑移失稳过程中电荷感应信号时频域各项前兆预警信息的分析可以知道,由于施工现场的复杂性和传感器布置的局限性,电荷感应信号在传播过程中会受到传播空间和传播介质等因素的影响,单个电荷预警指标无法全面反映滑移失稳过程中的断层演化信息。岩石滑移失稳前兆预警的关键难点在于认知破裂行为与各项参数演化规律和变化特征的内在联系,并获取多元化、有效的预警指标,构建综合性评估模型[44]。在此前提下,岩石动力灾害中多指标联合前兆预警是必然的发展趋势。
由于断层在失稳快速滑动前会经历较长的慢滑期,可以根据慢滑期电荷感应信号各项参量的演化特征对滑移失稳进行前兆预警。断层面微破裂存在局部集中成核现象,启滑后传感器与岩层位置也会发生较大改变,任何独立传感器都无法全面反映滑移全过程电荷产生情况,需要综合考虑所有信号。通过时频域多参量联合对比分析,建立以信号多通道择优数据(这个变量本质上是电荷感应数据的选择)(Z)、时域(T)和频域(P)为主体的电荷感应多参量监测模型如下式所示:
式中:D为多指标前兆评价结果。
图18为电荷感应多指标前兆预警系统,以A组为例,对试验水平加载开始后接收到的信号按照式(3)和图18进行前兆预警分析,可以有效获取滑移失稳前兆信息,判断滑移阶段。其中:
(1)多通道择优数据(Z):选择最接近成核区域、受外界环境影响较小和受断层滑移位置变化影响较小的通道进行电荷感应信号分析。
(2)时域(T):断层进入失稳快速滑移前,会经历较长的慢滑期,当信号出现多次电荷感应簇并出现最大值,每次电荷感应簇都伴随着分形维数的“先升维,后降维”现象,标志着滑移进入慢滑期的弹性变形阶段。当信号开始转变为小幅值密集信号。电荷感应累计值也从弹性变形阶段的“主体慢增,多点突增”转变为全面快速增加,分形维数也整体呈现为不断小幅降低时,标志着滑移进入启滑阶段。随后信号再次出现电荷脉冲簇并伴随着电荷累计速度的大幅提升和分形维数的大幅波动,标志着断层即将进入失稳快滑期。
(3)频域(P):开始主频区位于低频域,次主频区位于高频域,表明滑移处于弹性变形阶段。随后主频区和次主频区表现出“平移互换”现象,主频区右移至高频区域,次主频区则左移至低频区域,表明滑移处于启滑阶段。最后电荷感应簇只有低频段出现主频区,表明滑移即将失稳快滑期。与此同时,利用各阶段电荷信号主频均落于混叠域内的特点,联合小波变换在低频域上的分辨率优势和S变换在高频域上的分辨率优势,实时寻找时频谱峰值时间和频率信息与主频混叠域进行对比。
(1)岩石组合结构断层界面粗糙度和竖向荷载的增加都会使岩层滑移由稳滑向黏滑转变,并伴随有更多的荷大幅值电感应簇产生。当断层发生黏滑时,粗糙度的增加会使断层面启滑剪应力与峰值剪应力增加、黏滑周期缩短和黏滑事件增多。弹性变形阶段断层面出现局部微破裂成核导致电荷感应信号表现为多次大幅值电荷感应簇并出现最大值,进入启滑阶段则变为密集的小幅信号,并在快速滑移失稳前出现大幅值电荷感应簇。
(2)随断层界面粗糙度和竖向荷载增加,电荷累计速度和分形维数波动更为明显,且与电荷感应信号波形变化高度关联。弹性变形阶段电荷累计速度呈现“主体慢增,多点突增”,大破裂事件都伴随有分形维数“峰前升,峰后降”的大幅波动,主频区位于低频域,次主频区位于高频域,启滑阶段电荷累计速度转变为全面快速增加,分形维数整体表现出不断下降的趋势,主频区和次主频区表现出“平移互换”现象,主频区右移至高频区域,次主频区则左移至低频区域,且滑移各滑移阶段电荷信号主频均落于滑移过程共有频率混叠域内。
(3)对比滑移失稳前两阶段3种时频变换方法的时频分辨率与时频聚焦性,在低频区域,小波变换表现最好,短时傅里叶变换次之,S变换最差。在高频区域,S变换表现最好,小波变换次之,短时傅里叶变换最差。在滑移前两个阶段综合利用小波变换的低频信息和S变换的高频信息识别频区移动,可以更好地获取滑移失稳的时频前兆特征。
(4)断层滑移失稳过程中不同位置传感器电荷信号的差异在启滑前主要与局部集中微破裂引起的电荷特定区域聚集有关,在启滑后则主要由滑移面与传感器之间相对位置的错动变化引起。综合电荷感应信号空间特征和时频特征,建立以信号多通道择优数据(Z)、时域(T)和频域(P)为主体的电荷感应多指标监测模型,断层滑移电荷感应信号前兆监测的可靠性。
  • 国家自然科学基金面上项目(52474228)
  • 辽宁省教育厅基本科研项目(JYTZD2023078)
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2025年第46卷第11期
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doi: 10.16285/j.rsm.2024.1541
  • 接收时间:2024-12-16
  • 首发时间:2026-03-27
  • 出版时间:2025-11-14
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  • 收稿日期:2024-12-16
  • 录用日期:2025-04-03
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General Program of National Natural Science Foundation of China(52474228)
国家自然科学基金面上项目(52474228)
Foundation of Liaoning Province Department of Education(JYTZD2023078)
辽宁省教育厅基本科研项目(JYTZD2023078)
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    1.辽宁工程技术大学 力学与工程学院,辽宁 阜新 123000
    2.辽宁工程技术大学 理学院,辽宁 阜新 123000
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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
total species (%)

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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