Multi-model mine roof safety early warning model based on decision fusion

Abstract

The invention discloses a multi-model mine roof safety early warning model based on decision fusion. Real-time pressure monitoring data are collected through sensors, and an average value is selected as a training support pressure monitoring datum X1 to be used for establishing a support pressure submodel; stress distribution information of a coal bed or a rock stratum is collected through a leading pressure sensor to obtain a training leading pressure detection datum X2, and a leading pressure submodel is established; a separation layer indicator collects the separation layer situation of rock in a roof rock pillar near a working face and conducts processing to obtain a training roof separation layer monitoring datum X3, and a roof separation layer submodel is established; the data in the submodels are reconstructed to form corresponding prediction values, namely, Y1, Y2 and Y3, normalized decision fusion is conducted on the prediction values in a statistical recognition mode, and fused information is obtained. The multi-model mine roof safety early warning model is high in prediction and generalization capacity.

Description

technical field [0001] The invention belongs to the technical field of engineering safety, in particular to a multi-model mine roof safety early warning model based on decision fusion. Background technique [0002] With the shift of mine mining to the deep, affected by the advanced pressure of the working face, the stress of the surrounding rock of the roadway increases, the appearance of mine pressure intensifies, the scope of loosening expands, and the deformation of the roadway increases, especially in the areas containing gangue layers and along the gob near faults. The roadway brings great difficulties to the control of the surrounding rock of the roadway, and has a serious impact on the normal advancement of the working face. In view of the fact that the continuous large deformation of the ultra-thick coal seam roadway is difficult to control due to mining, it is necessary to conduct in-depth research on the dynamic pressure large deformation law of the coal seam roadw...

AI Technical Summary

Problems solved by technology

There are four main reasons for the analysis: 1. There are various monitoring methods for the mine roof, including electromagnetic radiation monitoring, micro-vibration monitoring, roof separation layer monitoring, roof pressure monitoring, etc. Various monitoring methods reflect the safety status of the mine roof from different angles, but The monitoring system does not integrate the early warning information, so it cannot give a comprehensive decision. When the forecast results are not uniform, it will cause false alarms and missed alarms, making it impossible to evaluate the safety status of the roof; 2. The monitoring of the roof status of the mine is only displayed as a monitoring chart , Many achievements in the study of rock formation movement and rock formation control are limited to the state of experience, the degree of intelligence is not high, and it cannot provide a scientific and reliable basis for the selection of roadway support methods and surrounding rock stress parameters; 3. The information fusion of multi-sensors Models and algorithms have achieved a lot of research results, but they fail to reflect the needs of actual industrial production; 4. Affected by complex factors such as production process and field operations, the effect of the method based on single model software measurement cannot reflect coal mine production The dynamic information and global characteristics of the process make the safety monitoring and forecasting poorly adaptable and cannot be used for a long time

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