Research on the Monitoring Law of Acoustic Emission Parameters during TBM Construction of Deep Hard Rock Tunnel

  • Zhang Yanjie ,
  • Zhang Rujiu ,
  • Zhao Tian ,
  • Liu Yaoru ,
  • Ouyang Lin
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  • 1. Yunnan Dianzhong Water Diversion Engineering Co., Ltd., Kunming 650000, P.R. China;
    2. State Key Laboratory of Hydroscience and Hydraulic Engineering, Tsinghua University, Beijing 100084, P.R. China;
    3. State Key Laboratory for Tunnel Engineering, China University of Mining and Technology (Beijing), Beijing 100083, P.R. China;
    4. Yunnan Water Diversion Project Construction Administration, Kunming 650051, P.R. China

Received date: 2025-11-19

  Online published: 2026-09-07

Abstract

On-site monitoring of deep hard rock tunnels can help understand the rockburst characteristics and provide timely warnings. Based on a deep-buried tunnel excavated by TBM, on-site acoustic emission (AE) monitoring was carried out to explore the AE waveforms and parameter characteristics of different sources (rockburst, TBM vibration, rock breaking of cutterhead, rock drilling of anchor drilling machine, etc.) under different AE sensor installation methods (drilling, tunnel wall, grouting anchors, foot anchors, steel bars). The results show that rockburst AE signals are characterized by short duration, high instantaneous energy (though lower total absolute energy than mechanical noise), and a relatively high peak frequency (several tens of kHz). The TBM vibration and excavation signals and rock drilling signals have extremely long duration, extremely high ringing count and absolute energy greater than that of rockburst signals. The rock-breaking signals from the cutterhead and anchor drilling machine are low-frequency signals with a peak frequency of only a few kHz, while the TBM vibration signals have the highest peak frequency (>120 kHz). The ringing count and energy rate slowly increase 10 minutes before rockburst, and there is a short quiet period when approaching rockburst. At the moment of rockburst, the ringing count and energy rate suddenly increase and reach their peak, and various frequency band signals appear, with a large number of low-frequency signals below 10 kHz. The AE b value significantly decreases to around 1.5. The influencing degree of TBM excavation noise on the AE ringing count and energy under different installation methods is in the order of steel bars>anchor rods>tunnel walls>inside the drilling hole, while the peak frequency characteristics are the opposite. AE technology is mainly suitable for rockburst monitoring during TBM shutdown. If drilling conditions cannot be met or more attention is paid to the temporal characteristics of AE parameters, AE sensors can be installed on anchoring structures such as grouting anchors and foot anchors (waveguide rods) to monitor and amplify AE signals. The research results in this study can provide a reference for AE monitoring methods and result analysis of similar deep-buried tunnels excavated by TBM.

Cite this article

Zhang Yanjie , Zhang Rujiu , Zhao Tian , Liu Yaoru , Ouyang Lin . Research on the Monitoring Law of Acoustic Emission Parameters during TBM Construction of Deep Hard Rock Tunnel[J]. Chinese Journal of Underground Space and Engineering, 2026 , 22(4) : 1428 -1439 . DOI: 10.20174/j.JUSE.2026.04.31

References

[1] Feng X T, Yang C X, Kong R, et al. Excavation-induced deep hard rock fracturing: Methodology and applications[J]. Journal of Rock Mechanics and Geotechnical Engineering, 2022, 14(1): 1-34.
[2] 李立民. 秦岭输水隧洞微震活动特征研究[J]. 地下空间与工程学报, 2021, 17(5): 1622-1629. (Li Limin. Research on the characteristics of microseismic activity in Qinling Water Diversion Tunnel[J] Chinese Journal of Underground Space and Engineering, 2021, 17(5): 1622-1629. (in Chinese))
[3] 欧阳林, 张如九, 刘耀儒, 等. 深埋隧洞岩爆防控技术及典型工程应用现状综述[J]. 长江科学院院报, 2022, 39(12): 161-170. (Ou Yanglin, Zhang Rujiu, Liu Yaoru, et al. Review on rockburst prevention techniques and typical applications in deep tunnels[J] Journal of Changjiang River Scientific Research Institute, 2022, 39(12): 161-170. (in Chinese))
[4] 张如九, 张延杰, 高仝, 等. 基于最大能量耗散率的岩爆倾向性指标研究[J]. 岩石力学与工程学报, 2023, 42(12): 2993-3009. (Zhang Rujiu, Zhang Yanjie, Gao Tong, et al. A novel index of rockburst proneness based on maximum energy dissipation rate[J]. Chinese Journal of Rock Mechanics and Engineering, 2023, 42(12): 2993-3009. (in Chinese))
[5] 侯靖, 张春生, 单治钢. 锦屏二级水电站深埋引水隧洞岩爆特征及防治措施[J]. 地下空间与工程学报, 2011, 7(6): 1251-1257. (Hou Jing, Zhang Chunsheng, Shan Zhigang. Rockburst characteristics and the control measures in the deep diversion tunnel of Jinping II hydropower station[J]. Chinese Journal of Underground Space and Engineering, 2011, 7(6): 1251-1257. (in Chinese))
[6] 谷明成, 何发亮, 陈成宗. 秦岭隧道岩爆的研究[J]. 岩石力学与工程学报, 2002(9): 1324-1329. (Gu Mingcheng, He Faliang, Chen Chengzong. Study on rockburst in Qinling tunnel[J]. Chinese Journal of Rock Mechanics and Engineering, 2002(9): 1324-1329. (in Chinese))
[7] 严健, 何川, 汪波, 等. 雅鲁藏布江缝合带深埋长大隧道群岩爆孕育及特征[J]. 岩石力学与工程学报, 2019, 38(4): 769-781. (Yan Jian, He Chuan, Wang Bo, et al. Inoculation and characters of rockbursts in extra-long and deep-lying tunnels located on Yarlung Zangbo suture[J]. Chinese Journal of Rock Mechanics and Engineering, 2019, 38(4): 769-781. (in Chinese))
[8] 冯夏庭, 陈炳瑞, 明华军, 等. 深埋隧洞岩爆孕育规律与机制:即时型岩爆[J]. 岩石力学与工程学报, 2012, 31(3): 433-444. (Feng Xiating, Chen Bingrui, Ming Huajun, et al. Evolution law and mechanism of rockbursts in deep tunnels: immediate rockburst[J]. Chinese Journal of Rock Mechanics and Engineering, 2012, 31(3): 433-444. (in Chinese))
[9] 陈炳瑞, 冯夏庭, 肖亚勋, 等. 深埋隧洞TBM施工过程围岩损伤演化声发射试验[J]. 岩石力学与工程学报, 2010, 29(8): 1562-1569. (Chen Bingrui, Feng Xiating, Xiao Yaxun, et al. Acoustic emission test on damage evolution of surrounding rock in deep-buried tunnel during TBM excavation[J]. Chinese Journal of Rock Mechanics and Engineering, 2010, 29(8): 1562-1569. (in Chinese))
[10] 魏秀琪, 唐春安, 张世超, 等. 秦岭隧洞4#支洞微震规律与岩爆预警研究[J]. 地下空间与工程学报, 2020, 16(6): 1866-1874. (Wei Xiuqi, Tang Chun'an, Zhang Shichao, et al. Research on rules of microseismicity and early warnings of rockburst in 4# branch tunnel of Qinling tunnel[J]. Chinese Journal of Underground Space and Engineering, 2020, 16(6): 1866-1874. (in Chinese))
[11] 李天斌, 许韦豪, 马春驰, 等. 基于深度学习的隧道微震监测及岩爆预警技术与系统研究[J]. 岩石力学与工程学报, 2024, 43(5): 1041-1063. (Li Tianbin, Xu Weihao, Ma Chunchi, et al. Research of technology and system of tunnel microseismic monitoring and rockburst early warning based on deep learning[J]. Chinese Journal of Rock Mechanics and Engineering, 2024, 43(5): 1041-1063. (in Chinese))
[12] Ma K, Shen Q Q, Sun X Y, et al. Rockburst prediction model using machine learning based on microseismic parameters of Qinling water conveyance tunnel. Journal of Central South University, 2023, 30: 289-305.
[13] Zhou X P, Peng S L, Zhang J Z, et al. Predictive acoustical behavior of rockburst phenomena in Gaoligongshan tunnel, Dulong river highway, China. Engineering Geology, 2018, 247: 117-128.
[14] Feng G L, Chen B R, Jiang Q, et al. Excavation-induced microseismicity and rockburst occurrence: Similarities and differences between deep parallel tunnels with alternating soft-hard strata. Journal of Central South University, 2021, 28: 582-594.
[15] Tang Z L, Liu X L, Xu Q J, et al. Stability evaluation of deep-buried TBM construction tunnel based on microseismic monitoring technology. Tunnelling and Underground Space Technology, 2018, 81: 512-524.
[16] 熊炎林, 陈冠甫, 刘晓丽. 深埋隧道微震事件规律及岩爆前兆微震信息研究[J]. 地下空间与工程学报, 2024, 20(4): 1375-1381. (Xiong Yanlin, Chen Guanfu, Liu Xiaoli. Research on microseismic event law of deep buried tunnel and microseismic information of rock burst precursor[J]. Chinese Journal of Underground Space and Engineering, 2024, 20(4): 1375-1381. (in Chinese))
[17] 刘宁, 张春生, 陈祥荣, 等. 深埋隧洞开挖围岩应力演化过程监测及特征研究[J]. 岩石力学与工程学报, 2011, 30(9): 1729-1737. (Liu Ning, Zhang Chunsheng, Chen Xiangrong, et al. Monitoring and characteristics study of stress evolution of surrounding rock during deep tunnel excavation[J]. Chinese Journal of Rock Mechanics and Engineering, 2011, 30(9): 1729-1737. (in Chinese))
[18] Li S J, Feng X T, Li Z H, et al. In situ monitoring of rockburst nucleation and evolution in the deeply buried tunnels of Jinping II hydropower station. Engineering Geology, 2012, 137-138: 85-96.
[19] 周春华, 李云安, 尹健民, 等. 电磁辐射法在某水电站岩爆监测中的工程应用[J]. 地下空间与工程学报, 2020, 16(3): 882-890. (Zhou Chunhua, Li Yunan, Yin Jianmin, et al. Electromagnetic radiation method for monitoring rockburst and its engineering application in a hydropower station[J]. Chinese Journal of Underground Space and Engineering, 2020, 16(3): 882-890. (in Chinese))
[20] 董陇军, 张凌云. 岩石破坏声发射b值的误差分析[J]. 长江科学院院报, 2020, 37(8): 75-81. (Dong Longjun, Zhang Lingyun. Error analysis of b-value of acoustic emission for rock fracture[J]. Journal of Changjiang River Scientific Research Institute, 2020, 37(8): 75-81. (in Chinese))
[21] Zhang R J, Liu Y R, Zhu L, et al. Failure characteristics and energy evolution process of delayed and instantaneous basalt rockburst under true triaxial conditions. International Journal of Rock Mechanics and Mining Sciences, 2024, 183: 105909.
[22] Zhang Q, Li X C, Gao J X, et al. Macro- and meso-damage evolution characteristics of coal using acoustic emission and Keuence testing technique. Natural Resources Research, 2022, 31: 517-534.
[23] 甘一雄, 吴顺川, 高艳华, 等. 不同传感器安装方式对隧道现场声发射参数监测结果的影响[J]. 科学技术与工程, 2020, 20(17): 7067-7073. (Gan Yixiong, Wu Shunchuan, Gao Yanhua, et al. Influence of the attaching methods of sensors on in-situ monitoring results of AE parameters in tunnels[J]. Science Technology and Engineering, 2020, 20(17): 7067-7073. (in Chinese))
[24] 田朝阳, 兰恒星, 张宁, 等. 某交通线路色季拉山隧道高地应力岩爆风险定量预测研究[J]. 工程地质学报, 2022,30(3): 621-634. (Tian Chaoyang, Lan Hengxing, Zhang Ning, et al. Quantitative prediction of rockburst risk in Sejila Tunnel of one railway[J]. Journal of Engineering Geology, 2022,30(3): 621-634. (in Chinese))
[25] 张艳博, 梁鹏, 田宝柱, 等. 花岗岩灾变声发射信号多参量耦合分析及主破裂前兆特征试验研究[J]. 岩石力学与工程学报, 2016, 35(11): 2248-2258. (Zhang Yanbo, Liang Peng, Tian Baozhu, et al. Multi parameter coupling analysis of acoustic emission signals of granite disaster and the precursor characteristics of the main rupture[J]. Chinese Journal of Rock Mechanics and Engineering, 2016, 35(11): 2248-2258. (in Chinese))
[26] Christian U, Masayasu O, Dimitrios G, et al.Acoustic emission testing: basics for research-applications in civil engineering[M]. Berlin Heidelberg: Springer Cham, 2008.
[27] 刘希灵, 刘周, 李夕兵, 等. 单轴压缩与劈裂荷载下灰岩声发射b值特性研究[J]. 岩土力学, 2019, 40(增1): 267-274. (Liu Xiling, Liu Zhou, Li Xibing, et al. Acoustic emission b-values of limestone under uniaxial compression and Brazilian splitting loads[J]. Rock and Soil Mechanics, 2019, 40(Supp.1): 267-274. (in Chinese))
[28] 杨东辉,乔伟,苏经纬,等.石灰岩脆性损伤演化和声发射特征研究[J].地下空间与工程学报,2024,20(5):1491-1502.(Yang Donghui,Qiao Wei,Su Jingwei,et al.Study on brittle damage evolution and acoustic emission characteristics of limestone[J].Chinese Journal of Underground Space and Engineering,2024,20(5):1491-1502.(in Chinese))
[29] 王超圣,蔡俊超,韩书娟,等.北山花岗岩声发射特征及破坏模式识别研究[J].地下空间与工程学报,2023,19(1):87-94.(Wang Chaosheng, Cai Junchao, Han Shujuan,et al.Study on acoustic emission characteristics and failure mode identification of Beishan granite[J].Chinese Journal of Underground Space and Engineering,2023,19(1):87-94.(in Chinese))
[30] 龚囱, 李长洪, 赵奎. 红砂岩短时蠕变声发射b值特征[J]. 煤炭学报, 2015, 40(增1): 85-92. (Gong Cong, Li Changhong, Zhao Kui. Study on b-value characteristics of acoustic emission of red sandstone during short-time creep process[J]. Journal of China Coal Society, 2015, 40(Supp.1): 85-92. (in Chinese))
[31] 蒋仕良. 波导杆对声发射信号的影响[J]. 无损检测, 2006(1): 51-52. (Jiang Shiliang. Influence of waveguide on acoustic emission signal[J]. Nondestructive Testing, 2006(1): 51-52. (in Chinese))
[32] Cheng W W, Wang W Y, Huang S Q, et al. Acoustic emission monitoring of rockbursts during TBM-excavated headrace tunneling at Jinping II hydropower station[J]. Journal of Rock Mechanics and Geotechnical Engineering, 2013, 5(6): 486-494.
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