微震
鉴定(生物学)
采矿工程
地质学
地震学
生物
生态学
作者
Yihan Zhang,Chenliang Hao,Longjun Dong,Zhongwei Pei,Fangzhen Fan,Marc Bascompta
标识
DOI:10.1016/j.ijmst.2025.07.007
摘要
The rock mass failure induced by deep mining exhibits pronounced spatial heterogeneity and diverse mechanisms, with its microseismic responses serving as effective indicators of regional failure evolution and instability mechanisms. Focusing on the Level VI stope sublayers in the Jinchuan #2 mining area, this study constructs a 24-parameter index system encompassing time-domain features, frequency-domain features, and multifractal characteristics. Through manifold learning, clustering analysis, and hybrid feature selection, 15 key indicators were extracted to construct a classification framework for failure responses. Integrated with focal mechanism inversion and numerical simulation, the failure patterns and corresponding instability mechanisms across different structural zones were further identified. The results reveal that multiscale microseismic characteristics exhibit clear regional similarities. Based on the morphological features of radar plots derived from the 15 indicators, acoustic responses were classified into four typical types, each reflecting distinct local failure mechanisms, stress conditions, and plastic zone evolution. Moreover, considering dominant instability factors and rupture modes, four representative rock mass instability models were proposed for typical failure zones within the stope. These findings provide theoretical guidance and methodological support for hazard prediction, structural optimization, and disturbance control in deep metal mining areas.
科研通智能强力驱动
Strongly Powered by AbleSci AI