摘要
为解决矿山相似模拟试验过程中测量自动化程度低、计算复杂、精度差等问题,提出了一种基于摄影测量计算机视觉方法,实现矿山相似材料模型自动监测的方法,该方法通过设计编码标志,实现对模型监测点的自动识别。鉴于矿山相似材料模型多为平面模型的事实,给出通过计算机视觉单应矩阵变换和基于物方的聚类匹配,实现对相似模拟模型自动变形观测,通过某大倾角厚煤层走向长壁综放相似模拟试验,验证了该方法的有效性。结果表明:所给方法除自动化程度高外,测量结果与全站仪所测监测点的平面精度相差0.001 m左右,所测位移场的下沉与水平移动均与实际变形情况一致,满足矿山岩层和地表移动相似模拟试验测量要求。
In orde to solve the problems of low degree of automation,complex calculation and poor precision in similar simulation experiments in mines,a method based on photogrammetric computer vision technology to realize automatic monitoring of mine similar material models is proposed.This method realizes the automatic identification of the model monitoring points by designing the coding marks.Based on the fact that the similar material model of the mine is mostly planar,the automatic deformation observation of the similar simulation model is realized by computer vision homograph matrix transformation and object-based cluster matching.The effectiveness of the method is verified by a similar simulation experiment of a longwall fully-mechanized caving with a thick dip angle.The results show that this method has the advantage of high automation degree.Besides,the measurement result is about 0.001 m different from the plane accuracy of the monitoring point measured by the total station.The sinking and horizontal movement of the measured displacement field is consistent with the actual deformation,which can meet the similar simulation experimental requirement of mine strata and ground movement.
作者
张春森
景啸宇
曹建涛
骆希娟
ZHANG Chunsen;JING Xiaoyu;CAO Jiantao;LUO Xijuan(College of Geomatics,Xi'an University of Science and Technology,Xi'an 710054,China;College of Energy Engineering,Xi'an University of Science and Technology,Xi'an 710054,China)
出处
《煤炭科学技术》
CAS
CSCD
北大核心
2019年第7期200-207,共8页
Coal Science and Technology
基金
陕西省自然科学基金资助项目(2018JM5103)
关键词
摄影测量
计算机视觉
相似模拟
编码识别
单应变换
photogrammetry
computer vision
similar simulation
code recognition
homograph transformation
