Intelligent prediction method for roof gas drainage roadway layout

Abstract

The roof gas drainage roadway, with its advantages of large flow and continuous extraction, is widely used in the gas control of high gas or outburst mine working faces. How to determine the reasonable arrangement position of the roof roadway to efficiently extract the pressure-relief gas in the goaf is key to ensuring the effect of gas control on the working face. Therefore, through a deep analysis of the arrangement principles of the roof gas drainage roadway and the main controlling factors of its arrangement position, an intelligent prediction method for the arrangement position of the roof gas drainage roadway based on the GA–BP neural network model is proposed. The prediction indicators of the GA–BP neural network model were determined using the grey correlation analysis method, and an intelligent prediction system for the arrangement position of the roof gas drainage roadway was designed and developed. The research results show: ① The mining thickness, burial depth, overlying rock structure, coal seam dip angle, and dip length of the working face are the main controlling factors for the arrangement position of the roof gas drainage roadway, and their weight values are ranked as: mining thickness > burial depth > overlying rock structure > coal seam dip angle > dip length; ② With the increase of genetic generations, the fitness of the GA–BP neural network continuously decreases, and when the genetic generation is 60, its fitness change is basically stable, indicating that the initial weight and bias of the GA–BP neural network are good; ③ Under the premise of the current training sample data set, the relative error of the prediction result of the arrangement position of the roof gas drainage roadway based on the GA–BP neural network model and the actual working condition value is only 0.43%～11.27%, which is within an acceptable range. This research can provide a certain reference for the precise design of the arrangement of the roof gas drainage roadway.

Keywords

• gas drainage
• roof gas drainage roadway
• precision arrangement
• genetic algorithm
• intelligent prediction