Full
Outline
The large range multi-level and multi-stope strength mining in deep metal mines causes frequent and violent adjustment of surrounding rock stress field, which is easy to induce engineering rock mass disasters such as spalling and caving. Aiming at the problems of high cost of multi-point test and poor timeliness in the inversion process of mining-induced stress field, an improved density clustering algorithm based on dynamic optimization of neighborhood search range of microseismic source radius was proposed, which divided microseismic activity into multiple clusters with high internal correlation. On this basis, the natural neighbor interpolation method was adopted to establish the inversion method of "microseismic signal apparent stress – microseismic event apparent stress – microseismic cluster apparent stress – mining-induced stress field". The engineering practice of deep metal mine shows that the average contour coefficient of microseismic data clustering cluster family is 0.56, which verifies the reliability of the improved density clustering algorithm for microseismic data clustering, and the apparent stress concentration area obtained by this method is highly consistent with the actual ground pressure disaster event area. The research results can provide theoretical and technical support for the identification and risk control of potential dangerous areas of mining-induced ground pressure in deep metal mines.
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| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
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