Evolution characteristics of an induced electric charge signal and identification method of charge for instability failure in loaded coal

Abstract

A coal-loaded charge induction monitoring system is developed to effectively forecast the dynamic disasters caused by coal failure. Specifically, a digital finite impulse response (FIR) filter is designed to denoise and filter the signal, and the time-frequency domain evolution of induced charge signals is analyzed during coal failure experiments. The quantitative relationships between the induced electric charge and stress-strain energy, and ultimately, between induced electric charge and coal deformation/failure, are revealed. Ultimately, the electric charge sensor exhibits high signal collection frequency and high sensitivity, and the FIR low-pass filter constructed in MATLAB effectively denoises and filters induced charge signals. The main frequency range of the white noise is 50–500 Hz, and the main frequency of the charge signal induced by coal deformation and failure is concentrated in the range of 0–50 Hz. The optimal distances for monitoring cubic and cylindrical raw coal samples using this sensor are 9 mm and 11 mm, respectively. Notably, strain energy is released faster when it can dissipate more readily, and induced charge pulses become denser when more intense signals produce large fluctuations. A method is proposed to identify coal deformation and failure based on changes in the induced electric charge. This study provides a new means of monitoring the early warning signs of dynamic coal mine disasters. Based on our experimental results and conclusions, a new method is proposed to identify coal deformation and failure based on changes in the induced electric charge. The precursor to the moment of coal failure can be identified by monitoring the amplitude of the induced charge, the dynamic trend of fluctuation, and the cumulative number of induced electric charge pulses during the process of coal deformation.