Abstract: Based on the concept of browser / server ( B / S) layered architecture design,combined with connection pooling,multi-threading,front and back-end separation and other technologies,a comprehensive monitoring and early warning system for ground pressure disasters with multiple sources of information such as acoustic emission,stress,displacement and microseismic Internet of Things (IoT) has been developed to address the problem of ground pressure disasters that are prone to occur after mines enter deep mining. The cumulative difference index and fuzzy comprehensive evaluation algorithm are used to analyze the acoustic emission parameters and establish a multi-index early warning model for acoustic emission,which is embedded in the Quartz timing task framework to realize the integration of real-time acoustic emission monitoring data and intelligent risk warning. Through the real-time disaster monitoring and early warning test of the filling body roof in the No. 2 layered stope of 1 018 m level Ⅴ panel of Jinchuan No. 2 mining area,the results show that:the early warning result of the acoustic emission cumulative difference multi-index comprehensive early warning model is consistent with the actual situation,which overcomes the defect of one-sided early warning of a single index and improves the reliability of early warning;The system realizes the functions of remote configuration of different types of equipment,automatic collection,analysis,early warning and visualization of monitoring data,and has important guiding significance for ground pressure disaster monitoring and early warning of deep broken roadways.

Key words: ground pressure disaster,monitoring and warning,system development,cumulative difference indicator,fuzzy comprehensive evaluation