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Research on the establishment of a mining subsidence prediction model under thick loose layer and its parameter inversion method
Investigación sobre el establecimiento de un modelo de predicción de subsidencia minera bajo una capa gruesa inestable y su método de inversión de parámetros
DOI:
https://doi.org/10.15446/esrj.v25n2.79537Keywords:
underground mining;, mining predict, probability integral model, geometric model, parameter inversion (en)minería subterránea, predicción de minería, modelo de probabilidad integral, modelo geométrico, inversión de parámetros (es)
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Most of the coal mining in China is underground, which will inevitably cause surface deformation and trigger a series of geological disasters. Therefore, it is essential to find a suitable method to forecast the ground sinking caused by underground mining. The most commonly used prediction model in China is the probability integral model (PIM). But when this model is used in the geological condition of mining under thick loose layers, the predicted edge of the sinking basin will converge faster than the actual measured sinking situation. A geometric model (GM) with a similar model shape as the PIM but with a larger boundary value was established in this paper to solve this problem. Then an improved cuckoo search algorithm (ICSA) was proposed in this paper to calculate the GM parameters. The stability and reliability of the ICSA were verified through a simulated working face. At last, the ICSA, in combination with the GM and the PIM, was used to fit 6 working faces with the geological mining condition of thick loose layers in the Huainan mining area. The results prove that GM can solve the above-mentioned PIM problem when it is used in geological mining conditions of thick loose layers. And it was obtained through comparative analysis that the GM and the PIM parameters can take the same value except for the main influence radius.
La mayor parte de la minería del carbón en China es subterránea, lo que inevitablemente causa deformaciones en la superficie y desencadena desastres geológicos. Por lo tanto, es necesario encontrar un método adecuado para pronosticar el hundimiento del suelo causado por la minería subterránea. El modelo de predicción más utilizado en China es el modelo integral de probabilidad (PIM). Pero cuando este modelo se utiliza en la condición geológica de la minería bajo capas gruesas inetables, el borde previsto de la cuenca de hundimiento converge más rápido que la situación de hundimiento medida. Para resolver este problema, en este artículo se estableció un modelo geométrico (GM) que tiene una forma de modelo similar a la del PIM pero que tiene un valor límite mayor. En este trabajo se propuso un algoritmo de búsqueda de cuco mejorado (ICSA) para calcular los parámetros de GM, y se verificó la estabilidad y confiabilidad del ICSA a través de una frente de trabajo simulado. Por último, el ICSA en combinación con el GM y el PIM se utilizaron para ajustar 6 caras de trabajo con la condición de minería geológica de capas gruesas sueltas en el área minera de Huainan. Los resultados demuestran que el GM puede resolver el problema de PIM mencionado anteriormente cuando se utiliza en las condiciones de minería geológica de capas gruesas inestables. Y se obtuvo mediante análisis comparativo que los parámetros del GM y del PIM pueden tomar el mismo valor excepto por el radio de influencia principal.
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