论文部分内容阅读
在利用CT层析成像方法重构回采工作面内地质构造等异常区分布时,受回采工作面客观条件影响,投影角度有限,只能采用一边发射信号对边接收的方法,导致投影数据不完备,系数矩阵高度稀疏,从而无法精确重构出工作面内部的地质构造及其分布.针对该问题,本文提出一种新的基于总变分正则化的先验约束加奇点模型重构算法,通过加入回采工作面两巷揭露的地质信息作为先验约束条件,同时对特定区域引入奇点模型以提高反演精度,锐化断层影响区域的边界.经过数值计算和回采工作面现场试验,证明该算法能显著提高重构图像的精度,锐化断层影响区域的范围,显著改善异常区的识别效果.
When using CT tomography to reconstruct the distribution of anomalous zones such as the geological structure in the working face, the projection angle is limited due to the objective conditions of the working face, and the projection method can not be used because the projection data is not perfect , The coefficient matrix is highly sparse, which can not accurately reconstruct the geological structure and its distribution within the working face.In order to solve this problem, this paper presents a new algorithm based on the total variation regularization of the prior constraint plus singular point model reconstruction, The geological information revealed by the two sides of working face is taken as a priori constraint condition and the singular point model is introduced to the specific region to improve the accuracy of inversion and to sharpen the boundary of the area affected by the fault.After numerical calculation and field test of working face, The algorithm can significantly improve the accuracy of the reconstructed image, sharpen the range of the affected area of the fault and significantly improve the recognition effect of the abnormal area.