Combining multiple monitoring methods can improve the accuracy of coal damage and fracture behavior detection. In this study, nine coal samples, each with similar P-wave velocities and masses, were subjected to joint monitoring experiments involving multiple physical parameters. The acoustic emission (AE) and resistance information of coal samples were assessed from the initiation of loading to eventual failure under diverse uniaxial loading rates. The characteristic electrical and acoustic parameters were analyzed in combination with coal damage conditions. The results show that, throughout the loading process, resistivity declined gradually with escalation of coal strain, followed by an abrupt nonlinear increase. Deformation before failure reduced coal resistivity by up to 11.39%. As the coal crack area expanded, the resistivity post-failure reached threefold the initial value. The AE ring count peak value corresponded to crack growth, and the AE energy had a power law distribution feature. The frequency band effect of the AE peak frequency was significant, and shear cracks accounted for more than 80%. Resistance and AE ring count exhibited simultaneous responses to coal failure, and the characteristic parameters of acoustic-electrical behavior demonstrated consistent patterns for cracks induced by various loading rates. The time sequence characteristics of the RSD index, which quantified the degree of resistivity fluctuation, corresponded almost exactly to the development process of coal damage described by AE, and the peak value of this index corresponded to the AE event in the time scale. The overall fluctuation degrees in resistivity of coal samples with varying damage levels showed positive correlation with the AE ring count. An acoustic-electric method for characterizing coal damage is summarized, and corresponding resistivity characteristic parameters are proposed. These parameters have a significant response law to coal damage, which is helpful in supplementing a new index for early warning of geological disasters.

多种监测方法的结合可以提高煤体损伤和断裂行为检测的准确性。在这项研究中，对具有相似纵波速度和质量的九个煤样进行了涉及多个物理参数的联合监测实验。在不同的单轴加载速率下，对煤样从加载开始到最终失效的声发射（AE）和阻力信息进行了评估。结合煤体损伤情况，对电声特征参数进行了分析。结果表明，在整个加载过程中，电阻率随着煤应变的增大而逐渐下降，随后出现非线性突变增加。破坏前变形使煤电阻率降低达11.39%。随着煤体裂隙面积的扩大，破坏后电阻率达到初始值的三倍。 AE环数峰值对应于裂纹扩展，AE能量具有幂律分布特征。 AE峰值频率的频带效应显着，剪切裂纹占80%以上。电阻和AE环计数表现出对煤破坏的同时响应，声电行为的特征参数表明不同加载速率引起的裂纹具有一致的模式。量化电阻率波动程度的RSD指数的时间序列特征与AE描述的煤害发展过程几乎完全对应，该指数的峰值对应于时间尺度上的AE事件。不同损伤程度煤样电阻率总体波动程度与AE环数呈正相关。 总结了一种表征煤体损伤的声电方法，并提出了相应的电阻率特征参数。这些参数对煤害具有显着的响应规律，有助于补充地质灾害预警的新指标。