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<p>Acoustic emission (AE) signals reflect the nonlinear damage evolution of rocks, and their interpretation and analysis are of great significance for understanding fracture mechanisms and providing instability warnings. In this study, sandstone specimens with varying strengths were subjected to uniaxial compression tests with the aid of AE monitoring. Based on multifractal theory, the nonlinear evolution of AE ring counts during loading was quantitatively characterized. By leveraging multifractal parameters, a novel cusp mutation model was introduced to effectively identify early precursors of violent rock failure. The results show that AE signals exhibit distinct multifractal behavior throughout the loading process, evolving from initial pore compaction to crack propagation and eventual macroscopic rupture. Also, the multifractal characteristic parameters can be regarded as state variables of the rock, exhibiting sudden spikes and declines as damage evolves toward instability. The developed model successfully detected early warning points prior to macroscopic rupture, exhibiting warning times 38.3&#xa0;s, 8.3&#xa0;s, 39.2&#xa0;s, and 6.9&#xa0;s, respectively, for the tested rock samples. These findings confirm that integrating multifractal parameters within cusp mutation theory enables accurate detection of instability precursors and provides a robust framework for early warning and hazard mitigation in rock engineering.</p>

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A multifractal fusion cusp model for detecting rock brittle failure precursors under uniaxial loading

  • 期刊论文

  • 发表日期：

    2026年6月29日

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  • Barkat Ullah,
  • Cuigang Chen,
  • Jifeng Yuan

摘要

Acoustic emission (AE) signals reflect the nonlinear damage evolution of rocks, and their interpretation and analysis are of great significance for understanding fracture mechanisms and providing instability warnings. In this study, sandstone specimens with varying strengths were subjected to uniaxial compression tests with the aid of AE monitoring. Based on multifractal theory, the nonlinear evolution of AE ring counts during loading was quantitatively characterized. By leveraging multifractal parameters, a novel cusp mutation model was introduced to effectively identify early precursors of violent rock failure. The results show that AE signals exhibit distinct multifractal behavior throughout the loading process, evolving from initial pore compaction to crack propagation and eventual macroscopic rupture. Also, the multifractal characteristic parameters can be regarded as state variables of the rock, exhibiting sudden spikes and declines as damage evolves toward instability. The developed model successfully detected early warning points prior to macroscopic rupture, exhibiting warning times 38.3 s, 8.3 s, 39.2 s, and 6.9 s, respectively, for the tested rock samples. These findings confirm that integrating multifractal parameters within cusp mutation theory enables accurate detection of instability precursors and provides a robust framework for early warning and hazard mitigation in rock engineering.