煤田地质与勘探2017，Vol.45Issue(5)：19-22,4.DOI:10.3969/j.issn.1001-1986.2017.05.004
基于图像识别的煤层井下宏观裂隙观测
Image recognition-based observation of macro fracture in coal seam in underground mine
摘要
Abstract
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.关键词
煤层/宏观裂隙/图像识别/几何模型Key words
coal seam/macro fracture/image recognition/geometric model分类
天文与地球科学引用本文复制引用
孙月龙,崔洪庆,关金锋..基于图像识别的煤层井下宏观裂隙观测[J].煤田地质与勘探,2017,45(5):19-22,4.基金项目
国家自然科学基金面上项目(41372160)The General Program of the National Natural Science Foundation of China(41372160) （41372160）
