Study on the features of coal rock failure potential signal based on multiscale multifractal analysis method
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摘要: 煤岩变形破坏诱发的表面电位信号包含损伤演化的关键信息，在煤岩动力灾害监测领域得到广泛研究，但大多是在单一时间维度对电位时序信号的波动特征进行研究，对时序信号的非线性、多尺度特征变化规律缺乏深入研究。针对该问题，搭建了煤岩破坏电位监测系统，同步测试了原煤和辉长岩2种试样的电位时序信号，并通过多尺度多重分形（MMA）法，深入研究了多尺度下的电位信号非线性特征，得到了电位时序信号的奇异性指数、奇异维数、局部赫斯特指数等参数，并采用L2范数对赫斯特曲面予以量化。实验结果表明：原煤和辉长岩的总体电位信号都呈现出多尺度多重分形特征，且裂纹萌生前后的电位多重分形图谱呈现一定差异性；相较于辉长岩，煤样在加载前后阶段不同位置处电位信号的奇异性指数差异Δα正负趋势呈现不同特征，表明了煤样具有更强的非线性演化特征；多尺度下局部赫斯特指数的L2范数更好地体现出试样不同通道电位信号间的长程相关性，并能够量化试样电位时序信号的非线性演化特征，进而实现煤岩失稳破坏预测。Abstract: The surface potential signals induced by the deformation and failure of coal and rock contain key information on damage evolution. It has been widely studied in the field of coal and rock dynamic disaster monitoring. However, most of these studies focus on the fluctuation features of potential time series signals in a single time dimension. There is a lack of in-depth research on the nonlinear and multiscale feature changes of the time series signals. To solve this problem, a monitoring system for the potential of coal and rock failure is built, and the potential time series signals of raw coal and gabbro samples are synchronously tested. Through the multiscale multifractal analysis (MMA) method, the nonlinear features of potential signals at multiple scales are studied in depth. The singularity index, singularity dimension, local Hurst index and other parameters of the potential time series signals are obtained. The Hurst surface is quantified by the L2 norm. The experimental results show that the overall potential signals of raw coal and gabbro show multiscale multifractal features, and the potential multifractal maps before and after crack initiation show some differences. Compared with gabbro, the positive and negative trends of the singularity index difference Δα of the potential signals of the coal samples at different positions in the pre-loading and post-loading phases show different features. It indicates a stronger non-linear evolution of the coal samples. The L2 norm of the local Hurst index at multiple scales better reflects the long-range correlation between different channel potential signals of the sample. It can quantify the nonlinear evolution features of the sample time series signals, thereby achieving the prediction of coal rock instability and failure.
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图 5 原煤通道1前后期及总体赫斯特曲面
Figure 5. Hurst surface of early, late and overall stage of raw coal's channel 1
图 6 原煤通道2前后期及总体赫斯特曲面
Figure 6. Hurst surface of early, late and overall stage of raw coal's channel 2
图 7 辉长岩通道1前后期及总体赫斯特曲面
Figure 7. Hurst surface of early, late and overall stage of gabbro's channel 1
图 8 辉长岩通道2前后期及总体赫斯特曲面
Figure 8. Hurst surface of early, late and overall stage of gabbro's channel 2
表 1 原煤与辉长岩物理力学特性
Table 1. Physical and mechanical properties of row coal and gabbro
试样 密度/ (g·cm−3) 弹性模量/GPa 峰值强度/MPa 原煤 1.19 2.00 14.55 辉长岩 2.92 14.84 75.22 
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表 2 不同通道各时期L2范数
Table 2. L2 norms of different periods in different channels
通道 d1 d2 d0 L2范数比值/% d1/d0 d2/d0 原煤通道1 16.16 15.28 14.96 108.02 102.14 原煤通道2 16.32 13.87 14.77 110.49 93.91 辉长岩通道1 15.35 18.02 16.56 92.69 108.82 辉长岩通道2 15.46 17.80 16.03 96.44 110.04
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[1] 谢和平,王金华,王国法,等. 煤炭革命新理念与煤炭科技发展构想[J]. 煤炭学报,2018,43(5):1187-1197.XIE Heping,WANG Jinhua,WANG Guofa,et al. New ideas of coal revolution and layout of coal science and technology development[J]. Journal of China Coal Society,2018,43(5):1187-1197. [2] WANG Chaojie,YANG Shengqiang,LI Xiaowei,et al. The correlation between dynamic phenomena of boreholes for outburst prediction and outburst risks during coal roadways driving[J]. Fuel,2018,231:307-316. doi: 10.1016/j.fuel.2018.05.109 [3] 齐庆新,潘一山,舒龙勇,等. 煤矿深部开采煤岩动力灾害多尺度分源防控理论与技术架构[J]. 煤炭学报,2018,43(7):1801-1810.QI Qingxin,PAN Yishan,SHU Longyong,et al. Theory and technical framework of prevention and control with different sources in multi-scales for coal and rock dynamic disasters in deep mining of coal mines[J]. Journal of China Coal Society,2018,43(7):1801-1810. [4] 谭云亮,郭伟耀,辛恒奇,等. 煤矿深部开采冲击地压监测解危关键技术研究[J]. 煤炭学报,2019,44(1):160-172.TAN Yunliang,GUO Weiyao,XIN Hengqi,et al. Key technology of rock burst monitoring and control in deep coal mining[J]. Journal of China Coal Society,2019,44(1):160-172. [5] 李楠,王恩元,GE Maochen. 微震监测技术及其在煤矿的应用现状与展望[J]. 煤炭学报,2017,42(增刊1):83-96.LI Nan,WANG Enyuan,GE Maochen. Microseismic monitoring technique and its applications at coal mines:present status and future prospects[J]. Journal of China Coal Society,2017,42(S1):83-96. [6] 王恩元,李忠辉,钮月,等. 深部煤层采动破坏电位响应特征与分布规律[J]. 煤田地质与勘探,2021,49(1):241-248.WANG Enyuan,LI Zhonghui,NIU Yue,et al. Characteristics and distribution laws of electric potential response to mining failure of deep coal seam[J]. Coal Geology & Exploration,2021,49(1):241-248. [7] 殷山. 煤岩受载破坏过程磁场效应规律实验研究[D]. 北京: 北京科技大学, 2022.YIN Shan. Experimental study on the law of magnetic field effect in the process of coal and rock failure under load[D]. Beijing: University of Science and Technology Beijing, 2022. [8] 陈丁. 矿井全空间巷道孔中瞬变电磁波场特征数值模拟研究[D]. 北京: 中国矿业大学（北京）, 2016.CHEN Ding. Study on wave field characteristics of drillhole transient electromagnetic in mine roadway whole space using numerical simulation[D]. Beijing: China University of Mining & Technology-Beijing, 2016. [9] 王昕. 基于电磁波技术的煤岩识别方法研究[D]. 徐州: 中国矿业大学, 2017.WANG Xin. Study of coal rock identification method based on electromagnetic wave technology[D]. Xuzhou: China University of Mining and Technology, 2017. [10] 杨志良,赵毅鑫,杨东辉,等. 单轴压缩条件下砂岩的声热效应特征研究[J]. 矿业科学学报,2019,4(3):230-239.YANG Zhiliang,ZHAO Yixin,YANG Donghui,et al. Study on the characteristics of the acoustic and the thermal effects of sandstone under uniaxial compression condition[J]. Journal of Mining Science and Technology,2019,4(3):230-239. [11] 孙海. 承载煤岩损伤演化的红外辐射响应机制及量化表征[D]. 徐州: 中国矿业大学, 2019.SUN Hai. Infrared radiation response mechanism and quantitative characterization during damage evolution of loading coal and rock[D]. Xuzhou: China University of Mining and Technology, 2019. [12] MIZUTANI H,ISHIDO T,YOKOKURA T,et al. Electrokinetic phenomena associated with earthquakes[J]. Geophysical Research Letters,1976,3(7):365-368. doi: 10.1029/GL003i007p00365 [13] 赵扬锋,刘力强,潘一山,等. 岩石变形破裂微震、电荷感应、自电位和声发射实验研究[J]. 岩石力学与工程学报,2017,36(1):107-123.ZHAO Yangfeng,LIU Liqiang,PAN Yishan,et al. Experiment study on microseismic,charge induction,self-potential and acoustic emission during fracture process of rocks[J]. Chinese Journal of Rock Mechanics and Engineering,2017,36(1):107-123. [14] ARCHER J,DOBBS M,AYDIN A,et al. Measurement and correlation of acoustic emissions and pressure stimulated voltages in rock using an electric potential sensor[J]. International Journal of Rock Mechanics and Mining Sciences,2016,8(9):26-33. [15] 郭伟红. 温变条件下岩石自然电位及激电特征研究[D]. 徐州: 中国矿业大学, 2021.GUO Weihong. Study on spontaneous potential and induced polarization characteristics of rock under temperature change[D]. Xuzhou: China University of Mining and Technology, 2021. [16] 殷山,李忠辉,钮月,等. 煤岩受载损伤演化电位特征实验研究[J]. 煤炭学报,2017,42(增刊1):97-103.YIN Shan,LI Zhonghui,NIU Yue,et al. Experimental study on the characteristics of potential for coal rock evolution under loading[J]. Journal of China Coal Society,2017,42(S1):97-103. [17] 吴小兵. 煤岩动力灾害的电势监测技术研究[J]. 山西焦煤科技,2018,42(增刊1):19-21,28.WU Xiaobing. Research on energy of position monitoring technology for coal and surrounding rock dynamic disaster[J]. Shanxi Coking Coal Science & Technology,2018,42(S1):19-21,28. [18] 孔艳慧,李忠辉,邱黎明,等. 突水过程煤岩表面电位变化规律研究[J]. 工矿自动化,2017,43(1):38-42.KONG Yanhui,LI Zhonghui,QIU Liming,et al. Research on variation rule of surface potential of coal rock during water-inrush process[J]. Industry and Mine Automation,2017,43(1):38-42. [19] 李忠辉. 受载煤体变形破裂表面电位效应及其机理的研究[J]. 中国矿业大学学报,2010,39(1):153-154.LI Zhonghui. Study on surface potential effect and its mechanism of coal during deformatoin and fracture under load[J]. Journal of China University of Mining & Technology,2010,39(1):153-154. [20] 刘杰,王恩元,李忠辉,等. 煤样破裂表面电位多重分形特征[J]. 煤炭学报,2013,38(9):1616-1620.LIU Jie,WANG Enyuan,LI Zhonghui,et al. Multi-fractal characteristics of surface potential of coal during the fracture[J]. Journal of China Coal Society,2013,38(9):1616-1620. [21] 钮月. 含瓦斯煤损伤破坏电位响应时空演化规律研究[D]. 徐州: 中国矿业大学, 2020.NIU Yue. Study on temporal and spatial evolution law of electric potential response of damage and failure of gas-bearing coal[D]. Xuzhou: China University of Mining and Technology, 2020. [22] 牛双建,靖洪文,杨大方,等. 单轴压缩下破裂岩样强度及变形特征[J]. 采矿与安全工程学报,2015,32(1):112-118,125.NIU Shuangjian,JING Hongwen,YANG Dafang,et al. Experimental study on strength characteristics and deformation behavior of the cracked rock samples under uniaxial compression[J]. Journal of Mining & Safety Engineering,2015,32(1):112-118,125. [23] 李楠,李保林,陈栋,等. 冲击破坏过程微震波形多重分形及其时变响应特征[J]. 中国矿业大学学报,2017,46(5):1007-1013.LI Nan,LI Baolin,CHEN Dong,et al. Multi-fractaland time-varying response characteristics of microseismic waves during the rockburst process[J]. Journal of China University of Mining & Technology,2017,46(5):1007-1013. [24] KANTELHARDT J W,ZSCHIEGNER S A,KOSCIELNY-BUNDE E,et al. Multifractal detrended fluctuation analysis of nonstationary time series[J]. Physica A:Statistical Mechanics and its Applications,2002,316(1-4):87-114. doi: 10.1016/S0378-4371(02)01383-3 [25] IHLEN E A F. Introduction to multifractal detrended fluctuation analysis in Matlab[J]. Frontiers in Physiology,2012,3(141):1-18. [26] KOKOSIŃSKA D, ŻEBROWSKI J J, BUCHNER T, et al. Asymmetric multiscale multifractal analysis （AMMA） of heart rate variability[J]. Physiological Measurement, 2021, 42（8）. DOI: 10.1088/1361-6579/ac184c. [27] 张艳丽. 癫痫脑电的分形分析及自动检测方法研究[D]. 青岛: 山东大学（青岛）, 2016.ZHANG Yanli. Research on fractal analysis of epileptic EEG and automatic seizure detection methods[D]. Qingdao: Shandong University, Qingdao, 2016. [28] ANDO M, NOBUKAWA S, KIKUCHI M, et al. Identification of electroencephalogram signals in Alzheimer's disease by multifractal and multiscale entropy analysis[J]. Frontiers in Neuroscience, 2021, 15. DOI: 10.3389/fnins.2021.667614. -
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