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Electromagnetic emission(EME) is a kind of physical phenomenon accompanying the process of deformation and fracture of loaded coal and rock and it is of importance in quantitatively analyzing its characteristics.This will reveal the process of deformation and fracture of coal and predicting dynamic disasters in coal mines.In this study,the G-P(Grassberger and Procaccia) algorithm,calculation steps of the(if only 1 dimension) correlation dimension of time series and the identification standards of chaotic signals are introduced.Furthermore,the correlation dimensions of EME and the acoustic emission(AE) signals of time series during deformation and fracture of coal bodies are calculated and analyzed.The results show that the time series of pulses number of EME and the time series of AE count rate are chaotic and that the saturation embedding dimensions of a K3 coal sample are,respectively,5 and 6.The results can be used to provide basic parameters for predicting of EME and AE time series.
Electromagnetic emission (EME) is a kind of physical phenomenon accompanying the process of deformation and fracture of loaded coal and rock and it is of importance in quantitatively analyzing its characteristics. This will reveal the process of deformation and fracture of coal and predicting dynamic disasters in coal mines. in this study, the GP (Grassberger and Procaccia) algorithm, calculation steps of (if only 1 dimension) correlation dimension of time series and the identification standards of chaotic signals were .Furthermore, the correlation dimensions of EME and the acoustic emission (AE) signals of time series during deformation and fracture of coal bodies are calculated and analyzed. results show that the time series of pulses number of EME and the time series of AE count rate are chaotic and that the saturation embedding dimensions of a K3 coal sample are, respectively, 5 and 6. The results can be used to provide basic parameters for predicting of EME and AE time series .