Abstract:
Water inrush in western China’s coal seam roofs is increasingly problematic due to complex geological conditions, with traditional warning methods proving ineffective. To address key challenges like indicator selection, warning methods, and standardization, research has focused on early warning theory, critical technologies, and intelligent platform development. First, a transparent hydrogeological model is introduced, building on the traditional geological model and incorporating dynamic updates. Second, based on the three-stage mechanism of water inrush development, indicator selection follows the principles of constraint, independence, and continuity. Five key factors are identified: surface water, aquifer structure and properties, aquiclude structure and properties, rock movement due to mining, and dynamic changes in hydrological elements. From these, 14 quantifiable indicators form the early warning system. Third, an intelligent early warning method is proposed using four indicators, establishing four warning levels, standards, and response measures based on accident cases, hydrological data, and standards. Fourth, an intelligent platform, integrating three layers and six core functions, is developed with a hybrid mechanism of triggers and polling for comprehensive evaluation and early warning. Finally, the platform was applied for a year in a western coal mine, issuing 15 warnings, including 10 for equipment anomalies and 5 for water inrush, all addressed with timely measures. The results validate the platform’s effectiveness. Future improvements will optimize the model and data analysis to enhance warning precision and speed.