Prediction of Floor Failure Depth in Deep Coal Mines by Regression Analysis of the Multi-factor Influence Index

Abstract

A multivariate regression analysis model was developed to predict floor failure depth in deep mines using field measured data from 39 coal mining sites in the eastern mining area of the north China coalfields. A Brillouin optical time domain reflectometry system was built with distributed optical fiber sensors embedded in the floor of a coalface to measure the actual failure depth of the mine floor. The measured and predicted results were in good agreement. This study provides an effective scientific basis for preventing and controlling floor water inrush in deep mines in the north China coalfield.