Rock burst early warning technology is currently applied mainly in microseismic monitoring. Rock burst signals indicate the micro-fracture phenomena of a rock and can transmit earthquake waves through the rock before they are finally received by a detector. A characteristic decomposition of rock micro-fracture signals was conducted by the singular value Empirical Mode Decomposition (EMD) algorithm to effectively decompose the characteristic signals of a rock micro-fracture from mixed microseismic signals, with a low signal to noise ratio to ensure prediction precision. When comparing the proposed method with wavelet decomposition and EMD, it was found that the local characteristics of the signals were retained effectively. The proposed algorithm was verified by applying it in a laboratory simulation and to the decomposition of microseismic signals from a hydro-power station. It was concluded that the improved algorithm had a better decomposition precision than wavelet decomposition and EMD decomposition and could effectively separate the characteristic signals of micro-earthquakes. This could provide a significant basis for the identification of the abnormal microseismic signals of rock micro-fractures as well as a pre-warning of rock fractures. It is therefore of practical significance to study rock fracture early warning technology.