Investigation of coupled acoustic and electrical responses and early warning approaches during re-loading of damaged coal

Abstract

Initial damage from engineering disturbances in deep coal mining degrades mechanical properties and heightens dynamic-hazard risks, challenging conventional monitoring. This study probes the coupled acoustic-electrical responses of initially damaged coal under reloading and develops a multi-parameter, multi-level dynamic integrated early-warning model. Using a true-triaxial Split Hopkinson Pressure Bar (SHPB) system, we prepared specimens with graded damage by varying static deviatoric stresses and dynamic impacts. Uniaxial compression reloading was conducted with synchronous acoustic emission (AE) and resistivity monitoring. Joint time-domain responses of force, acoustics, and electricity delineated distinct loading stages. Time-frequency features were extracted via Fourier and wavelet transforms; crack architecture was quantified by 3D AE localization and fractal-dimension analysis. Initial damage markedly reduced load-bearing capacity. Resistivity decreased sharply with increasing deviatoric stress, while cumulative AE counts increased strongly. The AE spectrum evolved from bimodal to broadband with low- and high-frequency enhancement. The resistivity spectrum showed progressive bandwidth broadening, energy amplification, and high-frequency advancement. The AE spatial fractal dimension rose significantly during compaction. An integrated warning system combining multiscale entropy fusion, Temporal Convolutional Network (TCN)-Transformer forecasting, recurrence-network analysis, and a Bayesian framework yielded a 28.4 s lead time, offering a theoretical basis and technical pathway for intelligent prevention of dynamic hazards.

Keywords

Acousto-electric coupling / Time-frequency analysis / Rockburst probability early warning / Multiscale entropy (MSE) / TCN-Transformer / Recurrence network

CRediT authorship contribution statement

Xiayan Zhang: Writing – review & editing, Writing – original draft, Visualization, Supervision, Resources, Project administration, Methodology, Investigation, Funding acquisition, Formal analysis, Data curation, Conceptualization. Enyuan Wang: Writing – review & editing, Funding acquisition. Rongxi Shen: Methodology, Investigation, Data curation. Huihan Yang: Writing – review & editing, Visualization, Validation. Haishan Jia: Visualization, Validation. Shenglei Zhao: Visualization, Validation. Zhoujie Gu: Visualization, Validation. Zhenhua Hu: Visualization, Validation. Chong Li: Visualization, Validation. Meng Wang: Visualization, Validation.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgements

The research reported in this paper was supported by the National Key Scientific Instruments and Equipment Development Projects of China (No. 52227901), the National Key R&D Program of China (No.2022YFC3004705), the Graduate Innovation Program of China University of Mining and Technology (No. 2024WLKXJ153), the Postgraduate Research & Practice Innovation Program of Jiangsu Province (No. KYCX24_2926), and the Special Funding for the Jiangsu Provincial Science and Technology Plan (No. BM2022013).

References

[1] Zhang CL, Wang PZ, Wang EY, Chen DP, Li C. Characteristics of coal resources in China and statistical analysis and preventive measures for coal mine accidents. Int J Coal Sci Technol 2023; 10(1):22.

[2] Kang HP, Gao FQ, Xu G, Ren HW. Mechanical behaviors of coal measures and ground control technologies for China’s deep coal mines—a review. J Rock Mech Geotech Eng 2023; 15(1):37-65.

[3] He MC, Wang Q. Rock dynamics in deep mining. Int J Min Sci Technol 2023; 33(9):1065-82.

[4] Askaripour M, Saeidi A, Rouleau A, Mercier—Langevin P. Rockburst in underground excavations: a review of mechanism, classification, and prediction methods. Undergr Space 2022; 7(4):577-607.

[5] Zheng QQ, Li PF, Xu Y, Cheng B, Hu H, Shi H, et al. Crack propagation and CT imaging of internal cracks in rocks damaged by pre—compression under explosive loading. Ain Shams Eng J 2025; 16(3):103302.

[6] Gu ZJ, Shen RX, Liu ZT, Zhao EL, Chen HL, Yuan ZC, et al. Dynamic characteristics of coal under triaxial constraints based on the split—Hopkinson pressure bar test system. Nat Resour Res 2023; 32(2):587-601.

[7] Shen RX, Gu ZJ, Liu ZT, Zhao EL, Zang ZS, Zhou X, et al. Study on impact dynamic behavior and failure characteristics of coal based on true triaxial split—Hopkinson pressure bar experiments. Nat Resour Res 2023; 32(6):2845—66.

[8] Wang HL, Liu D, Shan RL, Zhao Y, Li ZL, Tong X. Gradient failure mechanism and control technology of deep roadways under the action of deviatoric stress field. Heliyon 2024; 10(12):e32658.

[9] Dai LP, Feng DJ, Pan YS, Wang AW, Ma Y, Xiao YH, et al. Quantitative principles of dynamic interaction between rock support and surrounding rock in rockburst roadways. Int J Min Sci Technol 2025; 35(1):41-55.

[10] Huang P, Zhang JX, Damascene NJ, Wang ZJ, Li M. Effect of loading rate on mechanical behavior of coal samples with initial damage accumulation. Mech Time Depend Mater 2022; 26(2):309—22.

[11] Guo S, Huang P, Spearing AJSS, Wang ZJ, Dong XJ. An experimental study into the effects of cumulative energy damage on the mechanical properties of coal. Front Mater 2021; 8:733391.

[12] Huang P, Zhang JX, Spearing AJSS, Chai J, Dong CW. Experimental study of the creep properties of coal considering initial damage. Int J Rock Mech Min Sci 2021; 139:104629.

[13] Zhang L, Wang YM, Gao MZ, Jia WH, Xie SL, Hou W, et al. Spatio—temporal evolution of pore and fracture structures in coal induced by initial damage and creep behavior: a real—time NMR—based approach. Int J Min Sci Technol 2024; 34(10):1409—25.

[14] Wu YF, Song ZY, Wang Y, Li P, Zhou BK, Yang Z, et al. Behaviors of anthracite under differential cyclic loading (DCL) after wet and dry cycling: Deformability and hysteresis characteristics. Bull Eng Geol Environ 2024; 83(10):418.

[15] Li BT, Lin HF, Li SG, Wei ZY, Qin L, Wang P, et al. Exploration of pore structure evolution and damage mechanism of coal under liquid nitrogen freeze—thaw cycles. Fuel 2022; 325:124875.

[16] Wu MQ, Li HT, Wang L, Yang XL, Yang N, Yu MG. Compaction—deformation behaviors and breakage characteristics of loose broken coal under various stress—temperature coupling loads. Fuel 2023; 353:129083.

[17] Zhang X, Li ZH, Wang XR, Wang H, Li BL, Niu Y. Thermal effect on the fracture behavior of granite using acoustic emission and digital image correlation: an experimental investigation. Theor Appl Fract Mech 2022; 121:103540.

[18] Yang HZ, Wang EY, Cheng DQ, Wang XR, Li BL, Song Y, et al. Characteristics of energy evolution and acoustic emission response of concrete under the action of acidic drying—saturation processes cycle. J Build Eng 2023; 74:106928.

[19] Yang HZ, Wang EY, Wang XR, Song Y, Chen D, Wang DM, et al. Predicting the failure of rock using critical slowing down theory on acoustic emission characteristics. Eng Fail Anal 2024; 163:108474.

[20] Tian H, Li ZH, Aihemaiti A, Yin S, Gao FT. Investigation of dynamic failure behavior and acoustic emission frequency characteristics of sandstone under drop hammer impact. Bull Eng Geol Environ 2025; 84(6):315.

[21] Zhang QC, Li ZH, Niu Y, Yin S, Gao FT, Zhang FQ, et al. Acoustic emission response characteristics and energy evolution laws of sandstone under stepwise cyclic loading with ‘‘loading—stress maintaining—unloading”. Phys Fluids 2025; 37(6):067150.

[22] Wang XR, Wang JH, Liu XF, Zhou X, Li N, Feng JJ, et al. Microcracking evolution and clustering fractal characteristics in coal failure under multi step and cyclic loading. Eng Fract Mech 2024; 310:110511.

[23] Moradian Z, Einstein HH, Ballivy G. Detection of cracking levels in brittle rocks by parametric analysis of the acoustic emission signals. Rock Mech Rock Eng 2016; 49(3):785-800.

[24] Kong XG, Zhan MZ, Lin HF, Cai YC, Ji PF, He D, et al. Time—varying characteristics of acoustic emission and fractals based on information dimension during structural failure of coal subjected to uniaxial compression. Measurement 2024; 236:115088.

[25] Du K, Li XF, Tao M, Wang SF. Experimental study on acoustic emission (AE) characteristics and crack classification during rock fracture in several basic lab tests. Int J Rock Mech Min Sci 2020; 133:104411.

[26] Dong LJ, Zhang YH, Bi SJ, Ma J, Yan YH, Cao H. Uncertainty investigation for the classification of rock micro—fracture types using acoustic emission parameters. Int J Rock Mech Min Sci 2023; 162:105292.

[27] Korpisalo A. Geotomographic studies for ore explorations with the EMRE system. Measurement 2014; 48:232—47.

[28] Tan TJ, Wang EY, Wang XR, Yao WL. Study on the electrical impedance response and conductivity mechanism of coal mass rupture under impact load. Measurement 2023; 219:113164.

[29] Tan TJ, Wang EY, Wang XR, Ma LZ, Yao WL. Resistivity and damage of coal under cyclic loading and unloading. Eng Geol 2023; 323:107234.

[30] Hu QT, Liu SY, Li QG, Song MY, Zhang YB, Sun WJ, et al. Resistivity response characteristics of coal and coal—like materials under uniaxial compression. Energy Fuels 2024; 38(10):8598-611.

[31] Wang XY, Zhu GQ, Cheng DQ, Miao B, Chen FB, Tian H. Spatiotemporal evolution characteristics of apparent resistivity and its response correlation with acoustic emission of coal under multi—step loading. Sustainability 2022; 14(16):10061.

[32] Song MY, Li QG, Hu QT, Wu YQ, Ni GH, Xu YC, et al. Resistivity response of coal under hydraulic fracturing with different injection rates: a laboratory study. Int J Min Sci Technol 2022; 32(4):807-19.

[33] Song MY, Hu QT, Liu HH, Li QG, Zhang YB, Hu ZF, et al. Characterization and correlation of rock fracture—induced electrical resistance and acoustic emission. Rock Mech Rock Eng 2023; 56(9):6437—57.

[34] Song MY, Li QG, Hu QT, Zhang YB, Xu YC, Hu LP, et al. Evolution and correlation of acoustic emission and resistance parameters during coal fracture propagation. Nat Resour Res 2024; 33(5):2135—54.

[35] Chen GF, Liu XL, Song DQ, Wang EZ, Zhang RJ. Rockburst early warning based on microseism and critical point theory. Measurement 2024; 232:114715.

[36] Yu Q, Zhao DC, Xia YJ, Jin SJ, Zheng J, Meng QK, et al. Multivariate early warning method for rockburst monitoring based on microseismic activity characteristics. Front Earth Sci 2022; 10:837333.

[37] Di YY, Wang EY. Rock burst precursor electromagnetic radiation signal recognition method and early warning application based on recurrent neural networks. Rock Mech Rock Eng 2021; 54(3):1449-61.

[38] Yuan ZH, Ren FQ, Liu DQ. Experimental investigation on the infrared precursors of rockburst in sandstone with different bedding dip angles. Infrared Phys Technol 2023; 128:104518.

[39] Gong FQ, Luo S, Jiang Q, Xu L. Theoretical verification of the rationality of strain energy storage index as rockburst criterion based on linear energy storage law. J Rock Mech Geotech Eng 2022; 14(6):1737—46.

[40] Man Singh Basnet P, Mahtab S, Jin AB. A comprehensive review of intelligent machine learning based predicting methods in long—term and short—term rock burst prediction. Tunn Undergr Space Technol 2023; 142:105434.

[41] Ran QC, Liang YP, Ye CF, Ning YH, Ma TF, Kong FJ. Failure analysis of overlying strata during inclined coal seam mining: Insights from acoustic emission monitoring. Eng Fail Anal 2025; 182:110023.

[42] Du K, Bi RY, Sun Y, Yang CZ, Wang SY, Li GC, et al. Failure behaviors of granitic rocks induced by point/local loads under biaxial compression stress state. Acta Geotech 2023; 18(9):4645—69.

[43] Li HL, Shi JH, Li LJ, Tuo XG, Qu K, Rong WZ. Novel wavelet threshold denoising method to highlight the first break of noisy microseismic recordings. IEEE Trans Geosci Remote Sens 2022; 60:5910110.

[44] Barriga—Machado B, Hernández—Casamayor Á, Infante—García D, Giner E. Damage mechanism identification in additive manufactured extruded polymer via acoustic emission technique, experimental testing and pattern recognition models. Eng Fail Anal 2025; 181:109928.

[45] Zhang ZB, Wang EY, Li N, Zhang HT, Bai ZM, Zhang YH. Research on macroscopic mechanical properties and microscopic evolution characteristic of sandstone in thermal environment. Constr Build Mater 2023; 366:130152.

[46] Costa M, Goldberger AL, Peng CK. Multiscale entropy analysis of biological signals. Phys Rev E Stat Nonlin Soft Matter Phys 2005; 71(2 Pt 1):021906.

[47] Cao W, Meng Z, Li JM, Wu J, Fan FJ. A remaining useful life prediction method for rolling bearing based on TCN—transformer. IEEE Trans Instrum Meas 2025; 74:3501309.

[48] Peng XY, Dong HY, Zhang B. Echo State Network ship motion modeling prediction based on Kalman filter. 2017 IEEE International Conference on Mechatronics and Automation (ICMA). August 6—9, 2017, Takamatsu, Japan. IEEE, 2017:95-100.

[49] Diodati P, Marchesoni F, Piazza S. Acoustic emission from volcanic rocks: an example of self—organized criticality. Phys Rev Lett 1991; 67(17):2239-43.

[50] Haken H. Synergetics: an interdisciplinary approach to phenomena of self—organization. Geoforum 1985; 16(2):205—11.

[51] Zhang XN, Ding YL, Zhao HW, Yi LT, Guo T, Li AQ, et al. Mixed skewness probability modeling and extreme value predicting for physical system input—output based on full Bayesian generalized maximum—likelihood estimation. IEEE Trans Instrum Meas 2024; 73:2504516.