【摘要】：橋梁作為重要關(guān)鍵節(jié)點(diǎn),承擔(dān)著日益增長(zhǎng)的交通壓力,橋梁技術(shù)狀況直接關(guān)系交通和人身安全,進(jìn)行橋梁技術(shù)狀況評(píng)定尤為重要�；炷翗蛄翰『Φ淖畲蟊碚骶褪情_裂,以往采用人工借助橋檢車讀取裂縫寬度,難以準(zhǔn)確描述裂縫擴(kuò)展情況。以無(wú)人飛機(jī)成像獲得橋梁表面原始圖像,進(jìn)行分析處理,形成裂縫擴(kuò)展信息圖,既避免了人工精度誤差又提高了檢測(cè)速度,同時(shí)不受地形橋型橋?qū)挼南拗?有著重要的研究?jī)r(jià)值。本文研究了無(wú)人飛機(jī)橋梁檢測(cè)中成像角度修正問題,提出以三點(diǎn)激光器獲得三點(diǎn)物距,推導(dǎo)平均物距、被測(cè)平面相對(duì)夾角,對(duì)物距法獲得的像素解析度進(jìn)行修正。針對(duì)提出的無(wú)人飛機(jī)橋梁檢測(cè)成像特點(diǎn),基于形態(tài)學(xué)的組合濾波方法構(gòu)建了圖像預(yù)處理算法,增強(qiáng)圖像對(duì)比度,保護(hù)邊緣信息。對(duì)無(wú)人飛機(jī)成像圖像進(jìn)行邊緣識(shí)別,提出與Otsu相結(jié)合的Canny邊緣檢測(cè)算法,通過形態(tài)學(xué)判據(jù)消除微小噪點(diǎn),得到完整裂縫形態(tài)。針對(duì)裂縫形態(tài)提出基于最小二乘法擬合裂縫中心線的法向?qū)挾茸R(shí)別算法,并考慮特殊情況裂縫形態(tài)的識(shí)別分析,定義交叉裂縫交叉區(qū)域?qū)挾取＋@得具有工程實(shí)際意義的法向裂縫寬度,為基于無(wú)人飛機(jī)成像的橋梁技術(shù)狀況評(píng)定提供數(shù)據(jù)支持。本文最后進(jìn)行實(shí)橋檢測(cè)對(duì)比實(shí)驗(yàn),對(duì)湘潭市湘江二大橋進(jìn)行無(wú)人飛機(jī)成像裂縫識(shí)別,將寬度識(shí)別結(jié)果與第三方檢測(cè)機(jī)構(gòu)檢測(cè)數(shù)據(jù)進(jìn)行對(duì)比,結(jié)果表明無(wú)人飛機(jī)成像裂縫識(shí)別具有良好精度,并優(yōu)于人工橋梁裂縫檢測(cè)形成裂縫擴(kuò)展信息圖;滿足工程實(shí)際需要,具有工程應(yīng)用價(jià)值和發(fā)展?jié)摿Α?br/>[Abstract]:As an important key node, bridge bears increasing traffic pressure. The bridge technical condition is directly related to traffic and personal safety, so it is very important to evaluate the bridge technical condition. Crack is the biggest representation of concrete bridge disease. In the past, it is difficult to accurately describe the crack propagation by using manual aid of bridge inspection vehicle to read the crack width. The original image of bridge surface was obtained by unmanned aerial imaging, and the crack spreading information map was formed by analyzing and processing, which not only avoided the error of artificial precision, but also improved the detection speed, and was not limited by the width of topographic bridge at the same time. It has important research value. In this paper, the problem of imaging angle correction in the detection of unmanned aerial bridge is studied. It is proposed that the three-point laser is used to obtain the three-point distance, the average object distance is derived, the relative angle of the measured plane is derived, and the pixel resolution obtained by the object distance method is corrected. According to the characteristics of the bridge detection and imaging of unmanned aerial vehicle, the combined filtering method based on morphology is used to construct the image preprocessing algorithm to enhance the contrast of the image and protect the edge information. An edge detection algorithm based on Otsu and Otsu is proposed for edge recognition of UAV images. The tiny noise is eliminated by morphological criterion and the complete crack shape is obtained. A normal width recognition algorithm based on least square fitting of fracture center line is proposed for fracture morphology. The width of cross zone of cross fracture is defined by considering the identification and analysis of fracture shape in special cases. The normal crack width with practical engineering significance is obtained, which provides data support for bridge technical condition assessment based on UAV imaging. At the end of this paper, the actual bridge detection and contrast experiment are carried out, and the width recognition results are compared with the data of the third party detection mechanism. The image crack of the unmanned aircraft is identified by the Xiangjiang second Bridge in Xiangtan City. The results show that the imaging crack identification of unmanned aircraft has good accuracy and is superior to the artificial bridge crack detection to form the crack expansion information map, which meets the practical needs of engineering, and has engineering application value and development potential.
【學(xué)位授予單位】：湖南科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：U446

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