The failure and instability of deep coal-rock mass structures, which are influenced by mining disturbances, are major contributors to disasters like rock bursts. This study involved conducting indoor experiments using uniaxial loading test and acoustic emission (AE) experiments on indigenous primary coal-rock mass (PCRM). We utilize chaotic bifurcation based on strain energy to characterize the progressive damage stages of PCRM, demonstrating the chaotic characteristics of energy evolution during the gradual destruction process. The degree of damage resulting from PCRM failure was evaluated by jointly applying P-wave velocity tomography and AE event localization. Additionally, the classification of crack patterns in PCRM was conducted using the - correlation analysis method. The segmentation boundaries of crack classification patterns were then redefined using the Gaussian mixture model (GMM) algorithm. The research findings indicate that the chaotic bifurcation model of strain energy classifies stress into four stages: the stable region (Ⅰ), the metastable region (Ⅱ), the bifurcation region (Ⅲ), and the chaotic region (Ⅳ). The presence of a low-velocity zone in P-waves may indicate crack accumulation and damage within the system. Additionally, areas with abnormal P-wave velocities exhibit numerous AE events. The crack classification patterns of the four stages undergo an evolution from predominantly tensile cracks to a mixture of tensile and shear cracks, and the GMM algorithm successfully identifies the optimal separation path for crack classification boundaries. We propose an adaptive kernel density estimation (AKDE) algorithm to quantify the spatial distribution of AE events, thus offering a visual representation of the damage patterns at various stages.

中文翻译：

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揭示原生煤岩体样本的渐进破坏过程：来自能量演化、声发射裂纹模式和视觉表征的见解


受采矿扰动影响，深部煤岩体结构的破坏和失稳是造成冲击地压等灾害的主要原因。本研究涉及利用单轴加载试验和声发射（AE）试验对本土原生煤岩体（PCRM）进行室内实验。我们利用基于应变能的混沌分岔来表征PCRM的渐进损伤阶段，展示了渐进破坏过程中能量演化的混沌特征。通过联合应用纵波速度断层扫描和AE事件定位来评估PCRM失效造成的损坏程度。此外，PCRM 中的裂纹模式分类是使用相关分析方法进行的。然后使用高斯混合模型（GMM）算法重新定义裂纹分类模式的分割边界。研究结果表明，应变能混沌分岔模型将应力分为稳定区（Ⅰ）、亚稳区（Ⅱ）、分岔区（Ⅲ）和混沌区（Ⅳ）四个阶段。 P 波中低速区的存在可能表明系统内存在裂纹累积和损坏。此外，P 波速度异常的区域会出现大量 AE 事件。这四个阶段的裂纹分类模式经历了从以拉伸裂纹为主到拉伸和剪切裂纹混合的演变，并且GMM算法成功地识别了裂纹分类边界的最佳分离路径。我们提出了一种自适应核密度估计 (AKDE) 算法来量化 AE 事件的空间分布，从而提供各个阶段损伤模式的可视化表示。