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碎裂煤二维显微裂隙自动识别及信息提取
引用本文:夏红欣,屈争辉,卢晨刚,薛志文.碎裂煤二维显微裂隙自动识别及信息提取[J].煤田地质与勘探,2017,45(2):75-79.
作者姓名:夏红欣  屈争辉  卢晨刚  薛志文
基金项目:国家自然科学基金重点项目(41430317);国家自然科学基金青年科学基金项目(41302130);大学生创新创业计划(201410290034X)
摘    要:碎裂煤二维裂隙定量分析对构造复杂区煤储层渗透性、煤体强度有效预测有重要意义。针对2张分别取自不同变形程度碎裂煤的二维显微裂隙位图,基于MATLAB图像处理平台,经二值化、降噪和修复,编程实现裂隙自动识别,成功消除擦痕及大小不等杂斑干扰,识别裂隙与原裂隙趋于一致;然后在裂隙分割的基础上,实现了裂隙面积、长度、平均宽度及面裂隙率等参数的自动提取,并对2张位图获得的裂隙信息进行对比,结果与直观反映的裂隙发育程度一致。 

关 键 词:碎裂煤    二维    显微裂隙    自动识别    信息提取
收稿时间:2015-12-27

Automatic recognition and information extraction of two-dimensional micro cracks in cataclastic coal
Abstract:The quantitative analysis of two-dimensional cracks in cataclastic coal is important for the effective prediction of the permeability and the strength of coal mass of coal resevoir in structurally complicated areas. Aiming at the bitmaps of two-dimensional micro cracks in cataclastical coal with different deformation, on the basis of MATLAB image processing platform, through binaryzation, noise reduction and restoration, programming realized automatic recognition of cracks, eliminated succesfully the disturbance of stria and mottle unequal in size, the recognized cracks tended to be accordant to the original cracks. Then on the basis of crack partitioning, the automatic extraction of parameters such as area, length, mean width and surfacial crack rate was realized. The crack information taken from two bitmaps was compared, the result was accordant to the visual development degree of cracks. 
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