基于近景摄影测量的巷道表面位移监测
发布时间：2019-04-18 15:23
【摘要】：煤矿巷道表面位移的监测是巷道支护监测的主要内容,也是煤矿安全生产的重要保证。巷道表面位移监测主要包括顶板下沉量以及两帮移近量的监测,主要有两种方法:人工定期监测和有线/无线传感器的监测。但是人工定期监测的工程量比较大,测量步骤繁琐,精度不高;而传感器监测的成本比较高,通信机制比较复杂,易受到煤矿巷道环境的影响。针对上述情况,本文将近景摄影测量的方法应用到煤矿巷道中,对巷道的表面位移进行监测。主要包括以下三个部分的内容:煤矿巷道模型的搭建。本文首先根据煤矿巷道表面位移监测的内容,搭建了实验室模型,并对整个课题进行了总体规划。复杂背景下目标测点的提取。由于煤矿巷道内的环境比较复杂,放置的目标测点比较弱小,所以需要在复杂的巷道背景下提取出目标测点。先用直方图规定化对图像进行了简单的增强处理;然后利用基于Top-hat变换的形态学方法对图像进行滤波;最后再利用迭代方法求出图像的最佳分割阈值来分割图像,从而提取到了目标测点的坐标值。目标测点坐标的计算。煤矿巷道内的环境比较暗,而且地势比较复杂,用传统的摄像机标定的方法来获得摄像机的内方位元素和外方位元素已经不太适用。因此,使用以下的方法来获得摄像机的内参和外参:先对同一个矩形进行三次成像,利用矩形的几何约束条件来对摄像机进行自标定,进而确定摄像机的内方位元素;然后根据空间中任意平面在射影变换下的成像关系,确定单应矩阵,最后在单应矩阵构成的数学约束条件下来确定摄像机的外方位元素。得到了摄像机的内、外参数之后,目标测点的图像坐标值便可转换到世界坐标系中。在不同时刻对同一断面进行多次拍摄后,可求出巷道发生的位移。最后,在实验室中对巷道测点的位移进行了实验测量。实验结果表明,测量误差小于3.5%,在允许的误差范围之内,说明本课题设计方案确实可行。
[Abstract]:The monitoring of roadway surface displacement is not only the main content of roadway support monitoring, but also an important guarantee for safe production of coal mine. The monitoring of roadway surface displacement mainly includes the monitoring of roof subsidence and the displacement of two sides. There are two main methods: manual periodic monitoring and wired / wireless sensor monitoring. However, the engineering quantity of manual periodic monitoring is relatively large, the measuring steps are cumbersome, and the precision is not high, while the cost of sensor monitoring is relatively high, the communication mechanism is more complex, and it is easy to be affected by the environment of coal mine roadway. In view of the above situation, this paper applies the method of close-range photogrammetry to monitor the surface displacement of roadway in coal mine. Mainly includes the following three parts of the content: the construction of coal mine roadway model. In this paper, according to the content of coal mine roadway surface displacement monitoring, the laboratory model is set up, and the overall planning of the whole subject is carried out. Extraction of target measurement points under complex background. Because the environment in the coal mine roadway is more complex and the target measuring point is relatively weak, it is necessary to extract the target measuring point under the complicated background of the roadway. Firstly, the histogram normalization is used to enhance the image, and then the morphological method based on Top-hat transform is used to filter the image. Finally, the best segmentation threshold of the image is obtained by iterative method to segment the image, and then the coordinate value of the target measurement point is extracted. The calculation of the coordinate of the target measuring point. The environment in the coal mine roadway is relatively dark and the terrain is relatively complex. It is no longer suitable to obtain the inner and outer orientation elements of the camera by the traditional camera calibration method. Therefore, the following methods are used to obtain the internal and external parameters of the camera: first, the same rectangle is imaged three times, and the geometric constraints of the rectangle are used to self-calibrate the camera, and then the internal orientation element of the camera is determined; Then, according to the imaging relationship of any plane in space under projective transformation, the monoclinic matrix is determined. Finally, the external orientation element of the camera is determined under the mathematical constraint of the monoclinic matrix. After obtaining the inner and outer parameters of the camera, the image coordinate values of the target measurement point can be converted into the world coordinate system. After photographing the same section at different times, the displacement of the roadway can be obtained. Finally, the displacement of tunnel measuring points is measured experimentally in the laboratory. The experimental results show that the measurement error is less than 3.5%, which indicates that the design of this project is feasible within the allowable error range.
【学位授予单位】：太原理工大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：TP391.41
[Abstract]:The monitoring of roadway surface displacement is not only the main content of roadway support monitoring, but also an important guarantee for safe production of coal mine. The monitoring of roadway surface displacement mainly includes the monitoring of roof subsidence and the displacement of two sides. There are two main methods: manual periodic monitoring and wired / wireless sensor monitoring. However, the engineering quantity of manual periodic monitoring is relatively large, the measuring steps are cumbersome, and the precision is not high, while the cost of sensor monitoring is relatively high, the communication mechanism is more complex, and it is easy to be affected by the environment of coal mine roadway. In view of the above situation, this paper applies the method of close-range photogrammetry to monitor the surface displacement of roadway in coal mine. Mainly includes the following three parts of the content: the construction of coal mine roadway model. In this paper, according to the content of coal mine roadway surface displacement monitoring, the laboratory model is set up, and the overall planning of the whole subject is carried out. Extraction of target measurement points under complex background. Because the environment in the coal mine roadway is more complex and the target measuring point is relatively weak, it is necessary to extract the target measuring point under the complicated background of the roadway. Firstly, the histogram normalization is used to enhance the image, and then the morphological method based on Top-hat transform is used to filter the image. Finally, the best segmentation threshold of the image is obtained by iterative method to segment the image, and then the coordinate value of the target measurement point is extracted. The calculation of the coordinate of the target measuring point. The environment in the coal mine roadway is relatively dark and the terrain is relatively complex. It is no longer suitable to obtain the inner and outer orientation elements of the camera by the traditional camera calibration method. Therefore, the following methods are used to obtain the internal and external parameters of the camera: first, the same rectangle is imaged three times, and the geometric constraints of the rectangle are used to self-calibrate the camera, and then the internal orientation element of the camera is determined; Then, according to the imaging relationship of any plane in space under projective transformation, the monoclinic matrix is determined. Finally, the external orientation element of the camera is determined under the mathematical constraint of the monoclinic matrix. After obtaining the inner and outer parameters of the camera, the image coordinate values of the target measurement point can be converted into the world coordinate system. After photographing the same section at different times, the displacement of the roadway can be obtained. Finally, the displacement of tunnel measuring points is measured experimentally in the laboratory. The experimental results show that the measurement error is less than 3.5%, which indicates that the design of this project is feasible within the allowable error range.
【学位授予单位】：太原理工大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：TP391.41
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