基于图像识别的煤层井下宏观裂隙观测

煤层裂隙影响煤的力学性能和渗透性，且对于一个煤矿的安全生产具有重要意义。针对现有裂隙测量方法较低效且易受自然环境条件影响的问题，通过对煤壁裂隙拍照，结合数字图像处理技术，批量处理拍摄的照片，提取图片中的裂隙参数，得到煤壁上裂隙的倾角；然后根据采面、运输巷和回风巷之间的空间关系建立几何模型，可以求出裂隙的产状，为煤层裂隙系统的快速统计提供了一种新方法。经过实例验证，该方法高效准确且具有一定的实用性。 

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.