Abstract
In order to scientifically and reasonably assess the risk of water inrush from the coal seam floor, considering the influence of natural environmental factors such as hydrogeology, mining, and human intervention, the PSR model of ecosystem health evaluation was introduced, and the risk evaluation indicator system of water inrush from the coal seam floor was established. In order to solve the randomness and fuzziness of water inrush event evaluation, the evaluation model is constructed based on extension cloud theory and is applied in the 12123 working face of Pan Er coal mine of Huainan Mining Group. The application results show that the evaluation results are basically consistent with the actual situation, which shows that the model can be used in the actual evaluation work and is scientific.
Highlights
China is the most important coal producer and consumer in the world, and the proportion of coal consumption will remain above 50% for a long time
Through the statistical analysis of water inrush accident data, Shi et al concluded that when evaluating the risk of water inrush from the coal seam floor, the water inrush coefficient of the coal seam floor and the water content of aquifer should be considered at the same time and used support vector machines to establish a mine safety evaluation grade prediction model [8]
Rapport and Anthony Marcus Friend proposed the Pressure-State-Response (PSR) model in 1979, which was later developed by the Organization for Economic Co-operation and Development (OECD) and the United Nations Environment Program (UNEP) improvement and development [13]
Summary
China is the most important coal producer and consumer in the world, and the proportion of coal consumption will remain above 50% for a long time. Through the statistical analysis of water inrush accident data, Shi et al concluded that when evaluating the risk of water inrush from the coal seam floor, the water inrush coefficient of the coal seam floor and the water content of aquifer should be considered at the same time and used support vector machines to establish a mine safety evaluation grade prediction model [8]. Li et al established a floor water inrush evaluation model based on grey relational analysis and analytic hierarchy process [9]. Li et al used 8 kinds of water chemical components as indicators, combined with principal component analysis and Fisher discriminant analysis, to construct a water inrush water source identification model, and used the hydrological data of Xiandewang coal mine to verify the results. This paper uses the PSR model to establish the assessment indicator system of coal floor water inrush risk. In view of the randomness and fuzziness of water inrush events, the extension cloud theory is introduced to construct the assessment model, and the actual data of the site is collected to verify the validity of the model
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