Mine pressure big data real-time prediction system and method based on fully mechanized coal mining face

Abstract

The invention provides a mine pressure big data real-time prediction system and method based on a fully mechanized coal mining face and relates to the technical field of mine pressure. The system comprises an incoming pressure analysis module, a statistical calculation module, a prediction module and a display module, the incoming pressure analysis module analyzes support working cycle, divides working face support areas, divides working face incoming pressure and calculates incoming pressure step or stable step of a top plate at a support according to mine pressure big data; the statistical calculation module is used for counting all stable step pitches or incoming pressure step pitches of the top plate at the bracket position and fitting an incoming pressure probability curve; the prediction module predicts the roof incoming pressure probability of the support according to the incoming pressure probability curve and predicts the incoming pressure strength of the roof; and the displaymodule is used for displaying a support and support area roof pressure prediction result and a production prediction report including a single-support analysis and prediction comprehensive graph, anarea analysis and prediction comprehensive graph, a mine pressure prediction table and the like, and accurately predicts mining pressure by utilizing working face support mine pressure monitoring bigdata so as to guide roof management.

Description

technical field [0001] The invention relates to the technical field of mine pressure, in particular to a mine pressure big data real-time prediction system and method based on a fully mechanized mining face. Background technique [0002] In recent years, in coal mining, the process of automation and informatization of the working face has been accelerated, especially the degree of automation and informatization of the fully mechanized mining face has improved, which has led to the improvement of the safety and production efficiency of the working face. In the mining process of the fully mechanized mining face, due to the impact of the roof pressure, accidents such as roof fall and frame compression still occur from time to time. In addition, due to the increasing intelligence of the hydraulic support working resistance monitoring equipment reflecting the mine pressure of the fully mechanized mining face, the non-station type support working resistance monitoring system based...

AI Technical Summary

Problems solved by technology

In addition, due to the increasing intelligence of the hydraulic support working resistance monitoring equipment reflecting the mine pressure of the fully mechanized mining face, the non-station type support working resistance monitoring system based on the electro-hydraulic control hydraulic support has a large amount of data, and the working resistance monitoring of the working face support has entered the In the era of big data, the processing and application of monitoring data obviously cannot meet the needs of monitoring data processing, and the mining of monitoring data is of great significance to the roof control and roof control design in the coal mining production process

[0003] Usually the mine pressure monitoring sub-station collects a number every 6s, and the data volume of a support can reach 14,400 or more a day. For the monitoring data such as the working resistance of the massive supports in the working face, there is currently no effective means for deep excavation. Due to the influence of the specific mining environment of different coal mines, the traditional manual calculation prediction method has low prediction accuracy, time-consuming and low efficiency.

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