視覺計算在煤礦巷道變形監(jiān)測中的應(yīng)用研究
發(fā)布時間：2019-04-24 20:32
【摘要】：煤炭工業(yè)是我國最重要的基礎(chǔ)能源產(chǎn)業(yè),礦難事故的頻發(fā)引起了國家和社會對煤礦安全問題的高度重視。隨著視頻監(jiān)控技術(shù)的快速發(fā)展,視頻監(jiān)控技術(shù)已在煤炭安全生產(chǎn)監(jiān)測中得到廣泛應(yīng)用。本文主要研究了立體視覺測量中圖像特征點(diǎn)提取、攝像機(jī)標(biāo)定和重建點(diǎn)坐標(biāo)求解三個關(guān)鍵部分,并實(shí)驗應(yīng)用立體視覺測量方法監(jiān)測煤礦巷道形變。主要研究內(nèi)容和成果如下:首先研究了圖像上角點(diǎn)和光斑中心像點(diǎn)的提取方法。實(shí)驗對比了Harris、Shi-Tomasi和FAST三種角點(diǎn)檢測算法,結(jié)果表明:Harris算法對閾值敏感且易產(chǎn)生角點(diǎn)聚簇;FAST算法易提取到偽角點(diǎn)和產(chǎn)生角點(diǎn)聚簇;Shi-Tomasi算法能使檢測到角點(diǎn)分布均勻,避免角點(diǎn)聚簇,得出Shi-Tomasi算法適合十字靶標(biāo)角點(diǎn)像素級坐標(biāo)提取。通過圖像預(yù)處理由Canny邊緣檢測算法得到光斑單像素邊緣輪廓,利用最小二乘擬合法獲取光斑中心像點(diǎn)坐標(biāo)。其次對攝像機(jī)平面模板標(biāo)定法進(jìn)行了研究。由于通常計算單應(yīng)性矩陣時使用了畸變較大的像點(diǎn)影響了內(nèi)部和外部參數(shù)初值,從而影響了標(biāo)定精度。本文提出在計算單應(yīng)性矩陣時僅使用圖像中心附近像點(diǎn),使內(nèi)部參數(shù)和外部參數(shù)初值能更好地逼近準(zhǔn)確值,提高攝像機(jī)標(biāo)定精度。實(shí)驗證明此方法能提高攝像機(jī)標(biāo)定精度。然后針對立體視覺空間點(diǎn)坐標(biāo)求解問題,分析比對了三種常用求解方法:最小二乘法、公垂線段中點(diǎn)法、基于極線約束的重建方法,給出了以公垂線段為約束使反投影像點(diǎn)誤差最小的空間點(diǎn)坐標(biāo)求解方法,實(shí)驗證明該方法能提高空間點(diǎn)坐標(biāo)求解精度。最后將立體視覺測量技術(shù)應(yīng)用到巷道變形監(jiān)測中,給出了一種巷道變形監(jiān)測實(shí)施方案,實(shí)驗對巷道上監(jiān)測點(diǎn)位移進(jìn)行了測量,結(jié)果證明該視覺測量方案能準(zhǔn)確計算出巷道上監(jiān)測點(diǎn)空間位移,能對巷道變形進(jìn)行監(jiān)測。
[Abstract]:Coal industry is the most important basic energy industry in our country. The frequent occurrence of mine accidents has caused the state and society to attach great importance to the safety of coal mines. With the rapid development of video surveillance technology, video surveillance technology has been widely used in coal safety production monitoring. In this paper, the extraction of image feature points, camera calibration and the solution of reconstruction point coordinates in stereo vision measurement are studied, and the method of stereo vision measurement is used to monitor the deformation of coal mine roadway. The main contents and achievements are as follows: firstly, the extraction method of corner and spot center image is studied. Three corner detection algorithms, Harris,Shi-Tomasi and FAST, are compared. The results show that Harris algorithm is sensitive to threshold and it is easy to generate corner cluster, FAST algorithm is easy to extract pseudo-corner and generate corner cluster, and FAST algorithm is easy to extract pseudo-corner and generate corner cluster. The Shi-Tomasi algorithm can make the corner distribution uniform and avoid the clustering of corner points. It is concluded that the Shi-Tomasi algorithm is suitable for pixel-level coordinate extraction of cross-target corner points. The single pixel edge contour of the spot is obtained by the Canny edge detection algorithm, and the coordinates of the spot center image are obtained by the least square fitting method. Secondly, the camera plane template calibration method is studied. Since the large distortion image points are usually used in the calculation of the monotonic matrix, the initial values of internal and external parameters are affected and the calibration accuracy is affected. In this paper, it is proposed to use only image points near the image center in calculating the homomorphism matrix, so that the initial values of internal and external parameters can be better approximated to the exact values and the camera calibration accuracy can be improved. Experiments show that this method can improve camera calibration accuracy. Then, aiming at the point coordinate problem of stereo vision space, three common methods are analyzed and compared: least square method, middle point method of common vertical segment, and reconstruction method based on polar constraint. This paper presents a method for solving spatial point coordinates with the constraint of common vertical segment to minimize the error of back projection image points. The experimental results show that this method can improve the accuracy of spatial point coordinates. Finally, the stereo vision measurement technology is applied to the tunnel deformation monitoring, and a kind of tunnel deformation monitoring implementation scheme is given. The displacement of the monitoring points on the roadway is measured by experiments. The results show that the visual measurement scheme can accurately calculate the spatial displacement of the monitoring points on the roadway and can monitor the deformation of the roadway.
【學(xué)位授予單位】：西安科技大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2015
【分類號】：TD326;TP391.41
本文編號：2464762
[Abstract]:Coal industry is the most important basic energy industry in our country. The frequent occurrence of mine accidents has caused the state and society to attach great importance to the safety of coal mines. With the rapid development of video surveillance technology, video surveillance technology has been widely used in coal safety production monitoring. In this paper, the extraction of image feature points, camera calibration and the solution of reconstruction point coordinates in stereo vision measurement are studied, and the method of stereo vision measurement is used to monitor the deformation of coal mine roadway. The main contents and achievements are as follows: firstly, the extraction method of corner and spot center image is studied. Three corner detection algorithms, Harris,Shi-Tomasi and FAST, are compared. The results show that Harris algorithm is sensitive to threshold and it is easy to generate corner cluster, FAST algorithm is easy to extract pseudo-corner and generate corner cluster, and FAST algorithm is easy to extract pseudo-corner and generate corner cluster. The Shi-Tomasi algorithm can make the corner distribution uniform and avoid the clustering of corner points. It is concluded that the Shi-Tomasi algorithm is suitable for pixel-level coordinate extraction of cross-target corner points. The single pixel edge contour of the spot is obtained by the Canny edge detection algorithm, and the coordinates of the spot center image are obtained by the least square fitting method. Secondly, the camera plane template calibration method is studied. Since the large distortion image points are usually used in the calculation of the monotonic matrix, the initial values of internal and external parameters are affected and the calibration accuracy is affected. In this paper, it is proposed to use only image points near the image center in calculating the homomorphism matrix, so that the initial values of internal and external parameters can be better approximated to the exact values and the camera calibration accuracy can be improved. Experiments show that this method can improve camera calibration accuracy. Then, aiming at the point coordinate problem of stereo vision space, three common methods are analyzed and compared: least square method, middle point method of common vertical segment, and reconstruction method based on polar constraint. This paper presents a method for solving spatial point coordinates with the constraint of common vertical segment to minimize the error of back projection image points. The experimental results show that this method can improve the accuracy of spatial point coordinates. Finally, the stereo vision measurement technology is applied to the tunnel deformation monitoring, and a kind of tunnel deformation monitoring implementation scheme is given. The displacement of the monitoring points on the roadway is measured by experiments. The results show that the visual measurement scheme can accurately calculate the spatial displacement of the monitoring points on the roadway and can monitor the deformation of the roadway.
【學(xué)位授予單位】：西安科技大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2015
【分類號】：TD326;TP391.41
【引證文獻(xiàn)】
相關(guān)期刊論文 前1條
1 張俊義;;近距離測量在煤礦巷道變形監(jiān)測中的應(yīng)用研究[J];煤炭與化工;2017年09期
，本文編號：2464762
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