基于近景攝影測量的巷道表面位移監(jiān)測
發(fā)布時間：2019-04-18 15:23
【摘要】：煤礦巷道表面位移的監(jiān)測是巷道支護監(jiān)測的主要內(nèi)容,也是煤礦安全生產(chǎn)的重要保證。巷道表面位移監(jiān)測主要包括頂板下沉量以及兩幫移近量的監(jiān)測,主要有兩種方法:人工定期監(jiān)測和有線/無線傳感器的監(jiān)測。但是人工定期監(jiān)測的工程量比較大,測量步驟繁瑣,精度不高;而傳感器監(jiān)測的成本比較高,通信機制比較復(fù)雜,易受到煤礦巷道環(huán)境的影響。針對上述情況,本文將近景攝影測量的方法應(yīng)用到煤礦巷道中,對巷道的表面位移進行監(jiān)測。主要包括以下三個部分的內(nèi)容:煤礦巷道模型的搭建。本文首先根據(jù)煤礦巷道表面位移監(jiān)測的內(nèi)容,搭建了實驗室模型,并對整個課題進行了總體規(guī)劃。復(fù)雜背景下目標測點的提取。由于煤礦巷道內(nèi)的環(huán)境比較復(fù)雜,放置的目標測點比較弱小,所以需要在復(fù)雜的巷道背景下提取出目標測點。先用直方圖規(guī)定化對圖像進行了簡單的增強處理;然后利用基于Top-hat變換的形態(tài)學方法對圖像進行濾波;最后再利用迭代方法求出圖像的最佳分割閾值來分割圖像,從而提取到了目標測點的坐標值。目標測點坐標的計算。煤礦巷道內(nèi)的環(huán)境比較暗,而且地勢比較復(fù)雜,用傳統(tǒng)的攝像機標定的方法來獲得攝像機的內(nèi)方位元素和外方位元素已經(jīng)不太適用。因此,使用以下的方法來獲得攝像機的內(nèi)參和外參:先對同一個矩形進行三次成像,利用矩形的幾何約束條件來對攝像機進行自標定,進而確定攝像機的內(nèi)方位元素;然后根據(jù)空間中任意平面在射影變換下的成像關(guān)系,確定單應(yīng)矩陣,最后在單應(yīng)矩陣構(gòu)成的數(shù)學約束條件下來確定攝像機的外方位元素。得到了攝像機的內(nèi)、外參數(shù)之后,目標測點的圖像坐標值便可轉(zhuǎn)換到世界坐標系中。在不同時刻對同一斷面進行多次拍攝后,可求出巷道發(fā)生的位移。最后,在實驗室中對巷道測點的位移進行了實驗測量。實驗結(jié)果表明,測量誤差小于3.5%,在允許的誤差范圍之內(nèi),說明本課題設(shè)計方案確實可行。
[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.
【學位授予單位】：太原理工大學
【學位級別】：碩士
【學位授予年份】：2016
【分類號】：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.
【學位授予單位】：太原理工大學
【學位級別】：碩士
【學位授予年份】：2016
【分類號】：TP391.41
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