Holographic early warning method of mine dynamic disaster

Abstract

The invention provides a holographic early warning method of a mine dynamic disaster. A modal parameter set directly influencing occurrence of the mine dynamic disaster is used as an input variable set, the probability of occurrence of rock burst and the probability of occurrence of coal and gas outburst are used as output variables, and an artificial neural network model is built; samples are added to a learning sample database, and a holographic modal early warning device of the mine dynamic disaster is obtained; when early warning is conducted on any area of a mine, relevant information obtained in a mine experimental test and safe production is converted into input parameters of an early warning model by means of a holographic data mining converter, and then an early warning result isgiven by means of the holographic modal early warning device. By means of the holographic early warning method, holographic modal online prediction and early warning of the mine dynamic disaster can be achieved, and the system can achieve early warning separately based on the probability of occurrence of the rock burst accident and the probability of occurrence of the coal and gas outburst accident.

Description

technical field [0001] The invention relates to the technical field of disaster early warning and prevention of mines and underground engineering, in particular to a holographic early warning method for mine dynamic disasters. Background technique [0002] Mine dynamic disasters, including rockburst (rockburst), coal and gas outburst, water inrush, etc., are major mine disasters. Once such disasters occur, they will cause heavy losses to mine personnel and property. Therefore, the advance prediction, forecast and early warning of mine dynamic disasters are very important. Due to the many factors involved in mine dynamic disasters, there has not been a complete theoretical system for the occurrence mechanism, evolution process and induction mode of such disasters, nor has it formed a reliable monitoring, programming and high accuracy system. Early warning method. Most of the existing prediction and early warning methods mostly adopt the idea of ​​AHP, through the definition...

AI Technical Summary

Problems solved by technology

However, there are some deficiencies in these comprehensive weighting methods. For example, most of the selected early warning parameters are indirect parameters rather than direct parameters, such as mining depth, geological structure, production technology, ventilation mode, etc.; and many indirect parameters are related to certain A direct parameter is related, and not just a linear relationship, making it difficult to determine the weight

Even if some direct parameters are considered in the existing methods, such as impact tendency, prominence tendency, etc., there is no reasonable calculation method for these indicators. For example, the national standard GB / T 25217.2-2010 uses the weighted comprehensive evaluation method, there are Neither situation can be judged and the impact tendency result cannot be given.

Putting direct indicators and indirect indicators into one expression for weighting cannot reflect the hierarchical relationship of various indicators and the support for early warning results

The comprehensive weighting method cannot reflect the characteristics that the more signs, the greater the accident. Once the early warning parameter set is determined, new signs and manifestations will not be added. unscientific

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