Self-memorization Forecast Model For Deformation And Fracture Of Coal And Rock Based On Electromagnetic Emission Signals

Large number of home and abroad experimental researches indicate that, electromagnetic emission (EME) is in connect with deformation & fracture of coal--rock. Based on traits of EME, home scholars have proposed non-contact EME forecast technique. It is feasible to effectively forecast coal and rock dynamic catastrophes.However, on the spot, existent EME forecast is usually used for untime and fixed-point measurement, and to guarantee production without influence, measuring time is much short, as a result, continuous monitoring can't be achieved, which influences forecasting precision. Thus, the research core of thesis is how to promote forecast precision without continuous monitoringThe theme of thesis is Research on Self-memorization Forecast Model for Deformation and Fracture of Coal and rock Based on Electromagnetic Emission Signals, the aim of theesis is to establish a self-memorization forecast model, by aid of mathematical theory such as probability and mathematical statistics, matrix theory, advanced mathematics and etc, on the ground of on-site measured EME signals time-series. The research contents of thesis are as following:(1) Experimental researches on deformation and fracture EME of coal and rock. By aid of EME signals monitor and elastic buffer structure, experimental researches on EME of coal and rock samples has been done to explore the relation between variation of stress-strain and that of EME.(2) Inversion of non-linear ordinary differential equation for EME time-series. Based on measured EME time-series, then, set up a possible non-linear ordinary differential equation with self-memorization thought, and deduce the concrete format of equation with bi-directional differential.(3) Establishment of self-memorization model. Take non-linear ordinary differential equation as force core, and deduce a differential-integral equation with system self-memorization principle; work out self-memorization coefficients of equation's discretization format by means of least-square for self-memorization model.(4) Instance analysis. Apply above self-memorization model to forecast EME time-series of the other time quantums. Results indicate that self-memorization model has satisfying forecast effects. As are mentioned above all, forecast model of EME signals is constructed with self-memorization principle; it has satisfying effects, and provides a reference to forecast coal and rock dynamic catastrophes.