Gas outburst prediction early warning method based on big data platform

Abstract

The invention discloses a gas outburst prediction early warning method based on a big data platform. The method comprises the following steps: A, storing real-time monitoring data in an HDFS (Hadoop Distributed File System) of a Hadoop platform; B, preprocessing the real-time monitoring data by utilizing a linear exponential smoothing method; C, determining a period of the real-time monitoring data and detected outburst prevention data; D, taking the real-time monitoring data in one detection cycle as a data set; E, extracting monitoring data characteristic parameters in each data set; F, combining drilling gas inrush initial velocity qmax and maximum quantity of drilling yields smax with the monitoring data characteristic parameters so as to form gas outburst danger samples; G, performing gas outburst prediction by utilizing a BP neural network so as to obtain predicted values of the drilling gas inrush initial velocity qmax and maximum quantity of drilling yields smax; and H, comparing the predicted values with critical values of tunneling face outburst danger parameters, and judging whether early warning is needed. According to the method disclosed by the invention, the pre-control ability of gas outburst accidents in coal mines is improved.

Description

technical field [0001] The invention relates to the technical field of mine gas outburst prediction, in particular to a gas outburst prediction and early warning method based on a big data platform. Background technique [0002] Coal is the main body of energy in our country. At present, the safety production situation of coal mines in my country is quite severe. Safety problems such as gas outbursts and coal dust explosions have been restricting my country's coal production and seriously threatening the safety production of coal mines. Among the five natural disasters in coal mines, the outburst of coal and gas is extremely destructive and sudden, and it brings a series of serious consequences such as heavy casualties, property losses, and environmental damage. Therefore, one of the keys to realize safe production in coal mines is to effectively prevent coal and gas outbursts, and the key to preventing outbursts is to predict the coal bodies that are in danger of outbursts....

AI Technical Summary

Problems solved by technology

[0003] Although my country's coal mining enterprises are generally equipped with safety monitoring systems under the mandatory implementation of regulations, and some enterprises are equipped with safety monitoring systems and safety auxiliary decision-making systems at the same time, but at this stage, the prediction of coal and gas outburst is mainly based on monitoring data. For regional and daily forecasts, there is little follow-up processing of real-time monitoring data, and a large number of outburst prevention parameter data of manual inspections are not fully utilized

At the same time, the traditional coal mine gas outburst prediction and early warning platform generally has problems such as high research and development costs, limited data management and computing capacity, and lack of proper open and sharing functions.

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