Image recognition-based observation of macro fracture in coal seam in underground mine

The fracture has important influence on the mechanical properties and permeability of coal, and the fracture of coal seam has a great significance to the safe production of a mine. Faced with the existing fracture measurement method, which is inefficient and susceptible to natural environmental conditions, these images taken on coal wall were processed using digital image processing technology, then the fracture parameters were extracted and the angle will be got. A geometric model is established according to the spatial relationship between the mining face, transportation lane and return air lane, can be used to calculate the fracture occurrence, then provide a new method to rapidly measure occurrence. It is proved that the method is effective and accurate, and has certain practicality.