Failure Precursory Characteristics of Slope Model with Locked Section
-
摘要: 为探究花岗岩锁固段边坡模型损伤破坏过程中的微震信号能量、频率分布特征及临界慢化现象,开展了花岗岩锁固段边坡模型的破坏试验研究,利用单轴加载系统对不同岩桥角度的花岗岩锁固段边坡模型进行加载,采用应变片、微震(microseismic,MS)监测系统对其加载全过程进行同步观测.试验结果表明:(1)岩桥角对边坡模型的破坏形式产生影响,当岩桥角为70°和90°时破坏形式以拉张破坏为主;当岩桥角为110°时为拉压混合破坏;当岩桥角为130°时为压剪破坏,前缘蠕滑段为锁固型边坡变形最大的部位.(2)在加载过程中,当存在微小损伤破裂时,主要以高频、低能的微震信号为主,当产生大尺度损伤破裂时会伴随着低频、高能的微震信号.(3)在锁固段边坡模型处于临界破坏状态时会出现明显的临界慢化现象,表现为微震信号的方差、自相关系数产生突增现象,且突增点所对应的时间均达到失稳时间的80%,具有较好的时效性,可将微震信号的方差、自相关系数的突增作为边坡模型的失稳破坏前兆信息.(4)能量比方法与临界慢化理论形成联合预测判据,可克服单一判据的缺点,提高预测的准确性.该研究可为突发型的岩质边坡监测预警提供可用的参考价值.Abstract: In order to research the energy and frequency distribution characteristics of microseismic signals and the critical slowdown phenomenon in the damage and destruction process of granite locked section slope model, the damage test study of granite locked section slope model was carried out, and the granite locked section slope model with different rock bridge angles was loaded by uniaxial loading system, simultaneous observation was carried out by strain gauges and microseismic (MS) monitoring system. The test results manifest follows: (1) the rock bridge angle affects the damage form of the slope model, when the rock bridge angle is 70° and 90°, the damage form is mainly tension damage. When the rock bridge angle is 110°, it is mixed tension and compression damage. When the rock bridge angle is 130°, it is compression-shear damage, and the leading edge creep-slip section is the largest part of the locked slope deformation. (2) In the loading process, when there is a small damage rupture, mainly high-frequency, low-energy microseismic signals are dominant, and when a large-scale damage rupture is generated, it will be accompanied by low-frequency, high-energy microseismic signals. (3) The critical slowdown phenomenon occurs when the slope model in the locked section is in the critical damage state, which is manifested by the sudden increase of the variance and autocorrelation of the microseismic signal, and the time corresponding to the sudden increase reaches 80% of the destabilization time, so it has good timeliness, and the sudden increase of the variance and autocorrelation coefficient of the microseismic signal can be taken as the precursor information of the destabilization damage of the slope model. (4) The energy ratio method and critical slowing theory form a joint prediction criterion, which can overcome the shortcomings of single criterion and improve the accuracy of prediction. This study can provide usable reference values for monitoring and early warning of rocky slopes of sudden occurrence type.
-
表 1 小波变换结果
Table 1. Wavelet transform result
频段号 变换后信号 频宽(Hz) 1
2
3
4
5
6
7
8a7
d7
d6
d5
d4
d3
d2
d10~3.906 3
3.906 3~7.812 6
7.812 6~15.625 2
15.625 2~31.250 4
31.250 4~62.500 8
62.500 8~125.001 6
125.001 6~250.003 2
250.003 2~500.000 0 -
[1] Ai, D. H., Li, C. W., Zhao, Y. C., et al., 2020. Investigation on Micro-Seismic, Electromagnetic Radiation and Crack Propagation Characteristics of Coal under Static Loading. Rock and Soil Mechanics, 41(6): 2043-2051(in Chinese with English abstract). [2] Chen, Z. X., Yang, P., Liu, H. L., et al., 2019. Characteristics Analysis of Granular Landslide Using Shaking Table Model Test. Soil Dynamics and Earthquake Engineering, 126: 105761. https://doi.org/10.1016/j.soildyn.2019.105761 [3] Diks, C., Hommes, C., Wang, J. X., 2019. Critical Slowing down as an Early Warning Signal for Financial Crises? Empirical Economics, 57(4): 1201-1228. https://doi.org/10.1007/s00181-018-1527-3 [4] Ge, Y. F., Tang, H. M., Li, W., et al., 2016. Evaluation for Deposit Areas of Rock Avalanche Based on Features of Rock Mass Structure. Earth Science, 41(9): 1583-1592(in Chinese with English abstract). [5] Ge, Y. F., Zhou, T., Huo, S. L., et al., 2019. Energy Transfer Mechanism during Movement and Accumulation of Rockslide Avalanche. Earth Science, 44(11): 3939-3949(in Chinese with English abstract). [6] Hu, X. B., Fan, X. Y., Tang, J. J., 2019. Accumulation Characteristics and Energy Conversion of High-Speed and Long-Distance Landslide on the Basis of DEM: A Case Study of Sanxicun Landslide. Journal of Geomechanics, 25(4): 527-535(in Chinese with English abstract). [7] Huang, D., Cui, S., Li, X. Q., 2019. Wavelet Packet Analysis of Blasting Vibration Signal of Mountain Tunnel. Soil Dynamics and Earthquake Engineering, 117: 72-80. https://doi.org/10.1016/j.soildyn.2018.11.025. [8] Huang, D., Zhang, X. J., Gu, D. M., 2018. Failure Pattern and Evolution Mechanism of Locking Section in Rock Slope with Three-Section Landslide Mode. Chinese Journal of Geotechnical Engineering, 40(9): 1601-1609(in Chinese with English abstract). [9] Huang, R. Q., 2003. Study on the Mechanism of Typical Rock Landslides in Western China. Quaternary Sciences, 23(6): 640-647(in Chinese with English abstract). [10] Huang, R. Q., 2007. Large-Scale Landslides and Their Sliding Mechanisms in China since the 20th Century. Chinese Journal of Rock Mechanics and Engineering, 26(3): 433-454(in Chinese with English abstract). [11] Huang, R. Q., Chen, G. Q., Tang, P., 2017. Precursor Information of Locking Segment Landslides Based on Transient Characteristics. Chinese Journal of Rock Mechanics and Engineering, 36(3): 521-533(in Chinese with English abstract). [12] Kang, Y. M., Liu, H. Y., Aziz, M. M. A., et al., 2019. A Wavelet Transform Method for Studying the Energy Distribution Characteristics of Microseismicities Associated Rock Failure. Journal of Traffic and Transportation Engineering (English Edition), 6(6): 631-646. https://doi.org/10.1016/j.jtte.2018.03.007. [13] Lei, W. J., Wang, H. D., 2015. Characteristics of Wavelet Packet Energy Spectrum on Micro-Seismic Activities of Sandstone Samples under Uni-Axial Compressive Tests. Chinese Journal of Underground Space and Engineering, 11(5): 1111-1115(in Chinese with English abstract). [14] Li, H. R., Shen, R. X., Qiao, Y. F., et al., 2021. Acoustic Emission Signal Characteristics and Its Critical Slowing down Phenomenon during the Loading Process of Water-Bearing Sandstone. Journal of Applied Geophysics, 194: 104458. https://doi.org/10.1016/j.jappgeo.2021.104458 [15] Li, Y. L., Zhang, T. F., 2017. Study on Energy Identification Method of Seismic Instability Mechanism of Foundation Overburden Landslide. Journal of China and Foreign Highway, 37(5): 26-30(in Chinese with English abstract). [16] Liang, Z. Z., Xue, R. X., Xu, N. W., et al., 2020. Characterizing Rockbursts and Analysis on Frequency-Spectrum Evolutionary Law of Rockburst Precursor Based on Microseismic Monitoring. Tunnelling and Underground Space Technology, 105: 103564. https://doi.org/10.1016/j.tust.2020.103564 [17] Liu, H. D., Li, D. D., Wang, Z. F., et al., 2020. Physical Modeling on Failure Mechanism of Locked-Segment Landslides Triggered by Heavy Precipitation. Landslides, 17(2): 459-469. https://doi.org/10.1007/s10346-019-01288-3 [18] Lu, C. P., Dou, L. M., Liu, B., et al., 2012. Microseismic Low-Frequency Precursor Effect of Bursting Failure of Coal and Rock. Journal of Applied Geophysics, 79: 55-63. https://doi.org/10.1016/j.jappgeo.2011.12.013 [19] Maturana, M. I., Meisel, C., Dell, K., et al., 2020. Critical Slowing down as a Biomarker for Seizure Susceptibility. Nature Communications, 11(1): 2172. https://doi.org/10.1038/s41467-020-15908-3 [20] Spillmann, T., Maurer, H., Green, A. G., et al., 2007. Microseismic Investigation of an Unstable Mountain Slope in the Swiss Alps. Journal of Geophysical Research: Solid Earth, 112(B7): B07301. https://doi.org/10.1029/2006jb004723 [21] Tang, Z. H., Yu, X. L., Chai, B., et al., 2019. Energetic Criterion of Entering Acceleration in Progressive Failure Process of Bedding Rockslide: A Case Study for Shanshucao Landslide. Earth Science, 46(11): 4033-4042(in Chinese with English abstract). [22] van de Leemput, I. A., Wichers, M., Cramer, A. O. J., et al., 2014. Critical Slowing down as Early Warning for the Onset and Termination of Depression. Proceedings of the National Academy of Sciences of the United States of America, 111(1): 87-92. https://doi.org/10.1073/pnas.1312114110 [23] Wei, J. P., Jia, B., Wen, Z. H., et al., 2017. Study on Precursory Characteristics of Granite Failure Based on Infrasonic Energy. Results in Physics, 7: 2925-2932. https://doi.org/10.1016/j.rinp.2017.08.025 [24] Wei, Y., Li, Z. H., Kong, X. G., et al., 2018. Critical Slowing Characteristics of Sandstone under Uniaxial Compres-Sion Failure. Journal of China Coal Society, 43(2): 427-432(in Chinese with English abstract). [25] Wichers, M., Groot, P. C., Psychosystems, E. G., 2016. Critical Slowing down as a Personalized Early Warning Signal for Depression. Psychotherapy and Psychosomatics, 85(2): 114-116. https://doi.org/10.1159/000441458 [26] Wu, H., Hou, W., Zuo, D. D., et al., 2021. Early-Warning Signals of Drought-Flood State Transition over the Dongting Lake Basin Based on the Critical Slowing down Theory. Atmosphere, 12(8): 1082. https://doi.org/10.3390/atmos12081082 [27] Xu, Q., 2020. Understanding the Landslide Monitoring and Early Warning: Consideration to Practical Issues. Journal of Engineering Geology, 28(2): 360-374(in Chinese with English abstract). [28] Xu, Q., Peng, D. L., He, C. Y., et al., 2020. Theory and Method of Monitoring and Early Warning for Sudden Loess Landslide—A Case Study at Heifangtai Terrace. Journal of Engineering Geology, 28(1) : 111-121(in Chinese with English abstract). [29] Xu, X. F., Dou, L. M., Lu, C. P., et al., 2010. Frequency Spectrum Analysis on Micro-Seismic Signal of Rock Bursts Induced by Dynamic Disturbance. Mining Science and Technology (China), 20(5): 682-685. https://doi.org/10.1016/s1674-5264(09)60262-3 [30] Yfantis, G., Pytharouli, S., Lunn, R. J., et al., 2021. Microseismic Monitoring Illuminates Phases of Slope Failure in Soft Soils. Engineering Geology, 280: 105940. https://doi.org/10.1016/j.enggeo.2020.105940 [31] Zhang, X., Li, Z. H., Niu, Y., et al., 2019. An Experimental Study on the Precursory Characteristics of EP before Sandstone Failure Based on Critical Slowing Down. Journal of Applied Geophysics, 170: 103818. https://doi.org/10.1016/j.jappgeo.2019.103818 [32] Zhang, Y. B., Yu, G. Y., Tian, B. Z., et al., 2017. Identification of Multiple Precursor Information of Acoustic Emission Dominant Frequency in the Process of Granite Failure. Journal of Mining & Safety Engineering, 34(2): 355-362(in Chinese with English abstract). [33] Zhang, Z. H., Li, Y. C., Hu, L. H., et al., 2021. Predicting Rock Failure with the Critical Slowing down Theory. Engineering Geology, 280: 105960. https://doi.org/10.1016/j.enggeo.2020.105960 [34] Zhao, X. Y., Hu, K., Liang, Y., et al., 2018. Experiment on Sudden Departure Triggered by Shearing Vibration for Locked Segment of Wangjiayan Landslide. Chinese Journal of Rock Mechanics and Engineering, 37(1): 104-111(in Chinese with English abstract). [35] Zhao, Y. F., Jing, G., Fan, Y., et al., 2020. Experimental Study on the Microseism and Charge Signal Time-Frequency Characteristics in the Process of Fault Stick-Slip Instability. Chinese Journal of Rock Mechanics and Engineering, 39(7): 1385-1395(in Chinese with English abstract). [36] Zhao, Y. F., Liu, L. Q., Pan, Y. S., 2017. Experiment Study on Acoustic Emission, Microseism and Charge Induction during Fracture Process of Granite with Fault Zone under Uniaxial Compression. Seismology and Geology, 39(5): 964-980(in Chinese with English abstract). [37] 艾迪昊, 李成武, 赵越超, 等, 2020. 煤体静载破坏微震、电磁辐射及裂纹扩展特征研究. 岩土力学, 41(6): 2043-2051. https://www.cnki.com.cn/Article/CJFDTOTAL-YTLX202006029.htm [38] 葛云峰, 唐辉明, 李伟, 等, 2016. 基于岩体结构特征的高速远程滑坡致灾范围评价. 地球科学, 41(9): 1583-1592. doi: 10.3799/dqkx.2016.117 [39] 葛云峰, 周婷, 霍少磊, 等, 2019. 高速远程滑坡运动堆积过程中的能量传递机制. 地球科学, 44(11): 3939-3949. doi: 10.3799/dqkx.2017.589 [40] 胡晓波, 樊晓一, 唐俊杰, 2019. 基于离散元的高速远程滑坡运动堆积特征及能量转化研究——以三溪村滑坡为例. 地质力学学报, 25(4): 527-535. https://www.cnki.com.cn/Article/CJFDTOTAL-DZLX201904009.htm [41] 黄达, 张晓景, 顾东明, 2018. "三段式"岩石滑坡的锁固段破坏模式及演化机制. 岩土工程学报, 40(9): 1601-1609. https://www.cnki.com.cn/Article/CJFDTOTAL-YTGC201809006.htm [42] 黄润秋, 2003. 中国西部地区典型岩质滑坡机理研究. 第四纪研究, 23(6): 640-647. doi: 10.3321/j.issn:1001-7410.2003.06.007 [43] 黄润秋, 2007.20世纪以来中国的大型滑坡及其发生机制. 岩石力学与工程学报, 26(3): 433-454. doi: 10.3321/j.issn:1000-6915.2007.03.001 [44] 黄润秋, 陈国庆, 唐鹏, 2017. 基于动态演化特征的锁固段型岩质滑坡前兆信息研究. 岩石力学与工程学报, 36(3): 521-533. https://www.cnki.com.cn/Article/CJFDTOTAL-YSLX201703001.htm [45] 雷文杰, 王洪栋, 2015. 砂岩单轴压缩微震响应小波包能谱特征. 地下空间与工程学报, 11(5): 1111-1115. https://www.cnki.com.cn/Article/CJFDTOTAL-BASE201505004.htm [46] 李玉磊, 张腾飞, 2017. 基覆型滑坡地震失稳机制的能量判识方法研究. 中外公路, 37(5): 26-30. https://www.cnki.com.cn/Article/CJFDTOTAL-GWGL201705007.htm [47] 唐朝晖, 余小龙, 柴波, 等, 2021. 顺层岩质滑坡渐进破坏进入加速的能量学判据. 地球科学, 46(11): 4033-4042. doi: 10.3799/dqkx.2019.960 [48] 魏洋, 李忠辉, 孔祥国, 等, 2018. 砂岩单轴压缩破坏的临界慢化特征. 煤炭学报, 43(2): 427-432. https://www.cnki.com.cn/Article/CJFDTOTAL-MTXB201802016.htm [49] 许强, 2020. 对滑坡监测预警相关问题的认识与思考. 工程地质学报, 28(2): 360-374. https://www.cnki.com.cn/Article/CJFDTOTAL-GCDZ202002017.htm [50] 许强, 彭大雷, 何朝阳, 等, 2020. 突发型黄土滑坡监测预警理论方法研究——以甘肃黑方台为例. 工程地质学报, 28(1): 111-121. https://www.cnki.com.cn/Article/CJFDTOTAL-GCDZ202001013.htm [51] 张艳博, 于光远, 田宝柱, 等, 2017. 花岗岩破裂过程声发射主频多元前兆信息识别. 采矿与安全工程学报, 34(2): 355-362. https://www.cnki.com.cn/Article/CJFDTOTAL-KSYL201702023.htm [52] 赵晓彦, 胡凯, 梁瑶, 等, 2018. 王家岩滑坡锁固段剪切震动触发启程剧动试验. 岩石力学与工程学报, 37(1): 104-111. https://www.cnki.com.cn/Article/CJFDTOTAL-YSLX201801010.htm [53] 赵扬锋, 荆刚, 樊艺, 等, 2020. 断层黏滑失稳过程微震与电荷信号时频特征研究. 岩石力学与工程学报, 39(7): 1385-1395. https://www.cnki.com.cn/Article/CJFDTOTAL-YSLX202007008.htm [54] 赵扬锋, 刘力强, 潘一山, 2017. 单轴压缩下含断层带花岗岩声发射、微震和电荷感应实验. 地震地质, 39(5): 964-980. doi: 10.3969/j.issn.0253-4967.2017.05.007