Mine water inrush disaster prevention and control evaluation method based on fault water intelligent identification and early warning

CN119784149AActive Publication Date: 2025-04-08XINWEN MINING GROUP +1
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Patent Information

Application Number
CN202411842270.7
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2024-12-13
Publication Date
2025-04-08
Estimated Expiration
2044-12-13

AI Technical Summary

Technical Problem

The existing technology has shortcomings in terms of single monitoring parameters, insufficient intelligence of early warning models, low system integration, and passive prevention and control measures, making it difficult to effectively warn and control water outbursts on the coal mine base faults.

Method used

Using multi-dimensional fusion model, optimization algorithm, real-time data acquisition and intelligent control, an intelligent identification and early warning system based on fault water is constructed, including a bottom plate pressure-bearing water monitoring system, a multi-dimensional model early warning system and an intelligent hydrophobic system. Parameter weight calculation and water inrush risk warning are carried out through entropy weight method and PSO-SVM model.

Benefits of technology

The diversity of monitoring parameters and the real-time and dynamic nature of the intelligent early warning model are improved, the integration and coordination of the system are enhanced, more proactive and effective prevention and control measures are achieved, and the risk of coal mine flood disasters is reduced.

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Abstract

The invention discloses a mine water inrush disaster prevention and control evaluation method based on fault water intelligent identification and early warning, and relates to the technical field of mine water inrush disaster prevention and control. The method comprises the steps that firstly, a needed system is installed, then main parameters are selected through analysis, weight calculation is conducted on all the parameters through an entropy weight method, and the weight of each parameter is obtained through calculation; importing the weight of each parameter into a PSO-SVM model of the extended Toth model to form an extended Toth flow field model, namely an ETFM model, further extending to coal mine floor water inrush characteristics, and defining comprehensive water pressure field distribution Pt; and finally, obtaining a corresponding water inrush risk early warning value according to the game theory. By introducing a multi-dimensional fusion model, an optimization algorithm, real-time data acquisition and intelligent control, the technical problems of single monitoring parameter, insufficient intelligence of an early warning model, low system integration level, passive prevention and control measures and the like in a traditional method are solved.
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Citation Information

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