Comprehensive intelligent prediction method for predicting impact danger level based on micro-seismic fractal

Abstract

The invention discloses a comprehensive intelligent method for predicting an impact danger level based on micro-seismic fractal, and is applicable to the field of mine pressure impact prediction in the mine safety field. The method comprises three parts of micro-seismic fractal index input, fuzzy intelligent processing analysis and intelligent prediction result output. The method comprises specific steps of calculating micro-seismic time, space and energy fractal indexes, establishing an impact danger level membership matrix, establishing an index abnormity index and a Gaussian membership function, establishing a single-index evaluation matrix R, and calculating and updating each index weight matrix in real time by adopting an F value scoring method in a confusion matrix; calculating the membership probability of each impact danger level, and determining the final impact danger level by combining a maximum membership degree principle (MMDP) and a variable fuzzy feature recognition model (VFPR). The method is clear in mathematical model, high in universality and operability, capable of achieving intelligent probability prediction of different impact danger levels and intelligent recognition of comprehensive results, good in application feasibility and high in intelligent prediction efficiency.

Description

technical field [0001] The invention relates to a comprehensive intelligent prediction method, which is especially suitable for the comprehensive intelligent prediction method used in the field of mine safety field shock rock pressure prediction field based on microseismic fractal prediction of shock hazard level. Background technique [0002] Rock burst is a coal-rock dynamic disaster induced by mine earthquakes. It has become one of the most dangerous disasters faced by underground coal mining, and its prediction research has become one of the main components in the field of coal mine safety management. As a powerful and effective tool for monitoring mine earthquakes, microseismic has been widely used in the field of mine safety monitoring. Based on a large number of microseismic monitoring data, the research shows that microseismic events generally aggregate in time, space, and intensity distribution information before rock bursts occur. As an effective analysis method i...

AI Technical Summary

Problems solved by technology

In these studies, the current fractal dimension index is limited to describe the information of a single element among the three elements of microseisms, such as time, space and energy, which we call time capacity dimension, space capacity dimension and energy capacity dimension , the indicators are independent of each other, lacking the intersection and integration of the information of each element

At the same time, the quantified indicators only stay at the level of qualitative description in the actual prediction application of the possibility of shock occurrence, such as the abnormal low value of the index, the abnormal sharp drop, etc., which makes the prediction of rock burst difficult and inefficient.

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