Abstract
According to the No. 13 Mine of Pingdingshan Coal Co. Ltd., the fault dimension of the study area is calculated based on fractal theory. The four impact factors such as water inflow, water pressure, water inrush coefficient, and fault fractal dimension of 21 water boreholes are used as evaluation indices, and a mathematical model for identifying the water-filled source of the coal seam floor is established by coupling an entropy weight method and fuzzy variable set theory. The model is used to identify the water-filled source of 7 boreholes, which provide a reliable reference for the identification of the water-filled source. According to the calculation result of the entropy weight method, the water volume per unit of the borehole and the groundwater pressure have a significant impact on the water source identification, which accounts for 89.93% of the weight value. In the fuzzy variable set model, when the distance parameter p is 1 and the optimization criterion parameter α is 2, the accuracy of the water sample identification of the water source category to be identified is 85.71%, which is at a high recognition level. The more typical the impact factors selected and the more samples, the accuracy of water-filled source identification is much higher.
Highlights
The Pingdingshan coalfield is located in a North China typical coalfield area
Due to the influence of geological structures and coal mining disturbance, faults and fissures are developed in thin layer of limestone aquifers and aquicludes, which lead to a close hydraulic connection between the thin layer of limestones and the thick layer of limestone aquifers, so the coal seam mining process is threatened by the high-pressure aquifer of the bottom limestone
The representativeness of the established water-filled source identification model is related to the typical degree of the selected impact factor
Summary
The Pingdingshan coalfield is located in a North China typical coalfield area. At present, the No 2-1 coal seams of the Permian Shanxi formation are studied. Based on the distance discriminant analysis and grey system correlation degree method, the discriminant model of water-filled source identification was established, and the application test was carried out in the Xin’an mining area under similar hydrogeological conditions [6]. Zhang used laser-induced fluorescence technology as a means for identifying the water-filled source based on changes in water fluorescence caused by different parameters, such as water temperature and the flow rate of the water source [11] These achievements provide a reference for future generations to study the water-filled source of mines. Previous studies have used modern mathematical methods to establish identification models and identify water-filled sources using typical water chemical components, temperature, water level, etc. The key factors of water inrush are fully considered when the model is built, and the external disturbance is removed to the greatest extent, so as to accurately identify the water-filled source of the coal seam floor
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