Comprehensive Study on the Electrical Characteristics and Full-Spectrum Tracing of Water Sources in Water-Rich Coal Mines

Abstract

This study addresses the complex hydrogeological conditions and frequent inrush water incidents in the Donghuantuo coal mine by proposing a novel spectral tracing technique aimed at rapidly and accurately identifying the sources of inrush water. Through the analysis of electrical data from the Donghuantuo mine, the electrical characteristics of the mine floor were examined. Systematic sampling of water from the primary aquifers within the mining area was conducted, followed by detailed spectral measurements, resulting in the establishment of a spectral database for inrush water sources in the Donghuantuo mine. The chaotic sparrow search optimization algorithm (CSSOA) was employed to optimize the key parameters of the random forest (RF) model, leading to the development of the CSSOA-RF spectral tracing identification model. This model demonstrated outstanding classification performance in the test set, achieving an accuracy of 100%. This research offers a novel, more accurate, and reliable method for identifying the sources of inrush water, facilitating the rapid identification of sources in coal-bearing regions of North China and reducing disaster losses. Although the geological structure of the study area is relatively simple, the research achieved significant results in identifying both single and mixed water sources. However, further validation and optimization are needed for its applicability in more complex geological conditions. The findings of this study provide crucial technical support for safe mining operations and hold significant reference value for water hazard prevention in similar regions.

Keywords

• Donghuantuo mine
• identification of inrush water sources
• spectral tracing technology
• chaotic sparrow search optimization algorithm (CSSOA)