A method for predicting the damage degree of coal mining ground subsidence in flat terrain covered by loose layers

Abstract

The invention discloses a method for predicting the damage degree of ground collapse caused by mining of a single coal seam in a flat terrain area covered by a loose layer. Firstly, the prediction index of ground subsidence damage degree is selected to obtain its basic information. Secondly, according to the given ground subsidence prediction table, the ground subsidence of the working face in the area to be mined is predicted, and the degree of ground subsidence damage in the area to be mined is accurately and reliably quantified; finally, the degree of ground subsidence damage is evaluated based on the prediction results. The invention has the characteristics of quantification, image and simplicity, and has a realistic guiding effect on the restoration of the ecological environment in coal mining areas.

Description

technical field [0001] The invention belongs to the technical field of mine geological disasters, and in particular relates to a method for predicting the damage degree of ground subsidence in a coal mining area. Background technique [0002] Coal is the main one-time energy consumption in my country, accounting for more than 50% of energy utilization. While large-scale and high-intensity mining of coal, the ground subsidence caused by it has caused a huge impact on the ecological environment of the coal mining area. Therefore, a reasonable and scientific method for predicting the damage degree of ground subsidence is particularly important. [0003] Over the years, many scholars have done a lot of research on the ground subsidence induced by coal mining. Many feasible theories have been put forward, such as "BP neural network", "arctangent function", "gray correlation analysis" and so on. In addition, some researchers have used theoretical formulas in mathematics to esta...

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Problems solved by technology

[0004] However, these methods have certain deficiencies, mainly as follows: First, the mathematical model methods such as "BP neural network", "arctangent function", "gray correlation analysis" and so on are mostly risk assessment methods, generally used In order to evaluate whether a certain area will cause ground subsidence due to coal mining, there is no qualitative or quantitative analysis of the degree of ground subsidence damage during coal mining

Second, although the maximum development width and depth of surface fractures can be predicted through the theoretical prediction formula, the data required for the prediction are complex, diverse, difficult to obtain, and the calculation process is cumbersome, and the simplicity is poor, and only the topsoil is considered The nature of the coal seam does not consider the influence of conditions such as the depth of the coal seam, the thickness of the overlying bedrock, and the thickness of the coal mining.

The above methods more or less have the defects of low reliability, intuition, and lack of simplicity.

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