Study on key technology of identification of mine water inrush source by PSO-LightGBM

Abstract

Mine water inrush is a major type of disaster in coal mine production in China, it causes heavy casualties and serious economic losses and threatens coal mine safety. To quickly and accurately identify mine water inrush source, according to the hydrochemical characteristics of different aquifers in the Donghuantuo mining area, this paper systematically analyzes the hydraulic connection of the aquifers in main coal mining areas before and after mining activities. Collected four types of hydrochemical data of No. 5 coal seam roof water, No. 8 coal seam roof water, No. 122 coal seam floor water, and No. 1214 coal seam aquifer water in the Donghuantuo mining area. In addition, based on the hydrochemical data, the parameter selection of LightGBM was optimized by Particle Swarm Optimization (PSO) and constructed the PSO-LightGBM water inrush source identification model. The recognition accuracy of PSO-LightGBM model was compared with LightGBM model, classification regression tree (CART) model, and random forest (RF) model. The results showed that coal mining activities would have a significant impact on the water quality characteristics of the roof sandstone fissure water of No. 5 coal mine. Mining activities had a certain impact on the accuracy of the identification model. In addition, compared with the four recognition models, PSO-LightGBM model had the highest recognition accuracy of 97.22%. It showed that the model had high accuracy, stability, generalization ability, and important reference value for the identification of mine water inrush source.

Characteristics of Resistivity Variation in Deep Granite and In-Situ Detection Applications

“…As the temperature increases, the migration rate of conductive ions in the fracture water accelerates, leading to a gradual decrease in electrical resistivity, following an exponential decreasing trend. The relationship between temperature and electrical resistivity can be fitted using Equation (5). The temperature attenuation rate of rock resistivity is defined, and its calculation formula is given by Equation ( 6).…”

“…It can result in project delays and increased construction costs in less severe cases, while in more severe cases, it can lead to well flooding and abandonment. Both research and engineering practice have consistently shown that water hazards have become the primary risk in the construction of deep well projects [5][6][7][8] . Therefore, improving the accuracy and reliability of engineering geological and hydrogeological investigations within the vertical shaft project area is a prerequisite for scientifically assessing water inflow risks and effectively managing water disaster.…”

Identification of Limestone Aquifer Inrush Water Sources in Different Geological Ages Based on Trace Components

“…Human development is inseparable from energy consumption, and coal is the world's second largest energy source [1,2]. China has always been a country with coal as its main energy source and is currently the world's largest coal producer [3].…”

“…The machine learning model has obvious advantages when dealing with a large amount of data, but insufficient advantages in its recognition accuracy and the processing speed of a small amount of data, so the traditional water source identification method cannot be completely replaced. During the formation of coal mine water, it is subjected to various physical and chemical effects [2].…”