本文選題：露石水泥混凝土路面　切入點：構造深度　出處：《重慶交通大學》2015年碩士論文　論文類型：學位論文

【摘要】：露石水泥混凝土路面(EACCP)改善了普通水泥混凝土路面抗滑性能差、行車噪聲大、易產(chǎn)生眩光等方面的缺陷,擴展了水泥混凝土路面的應用領域。相對于普通水泥混凝土路面,EACCP表面具有豐富的微觀和宏觀構造,表面處理相對較為復雜,其表面質(zhì)量對路用性能有著決定性的作用。本文采用數(shù)字圖像技術通過對露石水泥混凝土路面的表面圖像的處理分析對其表面質(zhì)量進行評價,在路面表面圖像采集方法、圖像信息與路面構造深度關系、露石顆粒分離與識別、EACCP表面分布均勻性評價指標與評價方法等方面,進行了深入的理論分析與應用研究。本文通過分析采用數(shù)字圖像技術進行路面構造深度檢測的原理,總結了圖像采集過程中各種外界因素可能會對圖像分析產(chǎn)生的影響,并以此為基礎提出了規(guī)范化的圖像采集方法,提高圖像采集質(zhì)量,為進一步的圖像分析奠定了良好的基礎;將采集得到的圖像進行尺寸標定、裁切、平滑處理后,采用BP神經(jīng)網(wǎng)絡對EACCP表面圖像信息和鋪砂法實測路面構造深度的關系進行模擬,采用不同訓練方法對不同規(guī)模的網(wǎng)絡進行訓練,并對得到的網(wǎng)絡模型進行誤差分析,得到符合一定精度要求的關系模型。針對EACCP圖像中可能存在的露石顆粒與背景對比不明顯、亮度不均的問題,采用分塊-組合OTSU分割法,取得了較為理想的分割效果。采用數(shù)字圖像技術提取EACCP表面露石顆粒信息,對其數(shù)量、面積以及靜矩等指標進行計算分析,提出以被測表面露石顆粒數(shù)量、面積百分率的變異系數(shù)雙指標對EACCP表面均勻性評價的方法,并借鑒相關規(guī)范中對公路技術狀況的評價體系,提出路面均勻性狀況指數(shù)PUI的概念及其計算方法,完善了EACCP表面均勻性評價體系。在MATLAB程序設計平臺下對數(shù)字圖像技術進行構造深度檢測和露石表面均勻性檢測評價的方法進行程序設計,利用GUI設計工具將其功能集成于一個易于理解和操作圖形界面,并將其應用于重慶市涪陵區(qū)李渡鎮(zhèn)EACCP試驗路段表面質(zhì)量檢測和評價,驗證了利用數(shù)字圖像技術對EACCP表面構造深度測量、表面分布均勻性評價評價方法及程序界面的適應性。
[Abstract]:EAC CPC) improves the common cement concrete pavement with poor skid resistance, high driving noise and glare, etc. The application field of cement concrete pavement is expanded. Compared with ordinary cement concrete pavement, EACCP surface has abundant micro and macro structure, and surface treatment is relatively complex. The surface quality plays a decisive role in road performance. In this paper, digital image technology is used to evaluate the surface quality of exposed cement concrete pavement by processing and analyzing its surface image. The relationship between image information and pavement structure depth, the separation and identification of exposed rock particles, the evaluation index and evaluation method of surface distribution uniformity of EACCP, etc. This paper analyzes the principle of using digital image technology to detect the depth of pavement structure, and summarizes the influence of various external factors on image analysis in the process of image acquisition. On this basis, a standardized image acquisition method is proposed to improve the quality of image acquisition, which lays a good foundation for further image analysis. BP neural network is used to simulate the relationship between the surface image information of EACCP and the measured depth of pavement structure by sand laying method. Different training methods are used to train the network of different scales, and the error analysis of the obtained network model is carried out. The relation model which meets the requirement of certain precision is obtained. Aiming at the problem that the contrast between the exposed rock particles and the background is not obvious and the brightness is uneven in the EACCP image, a block-combinatorial OTSU segmentation method is adopted. The digital image technology is used to extract the information of exposed rock particles on the surface of EACCP, and the number, area and static moment of the information are calculated and analyzed, and the number of exposed rock particles on the measured surface is put forward. The method of evaluating the surface uniformity of EACCP by double index of variation coefficient of area percentage, and referring to the evaluation system of highway technical condition in relevant codes, the concept and calculation method of pavement uniform property condition index (PUI) are put forward. The evaluation system of surface uniformity of EACCP is perfected. The methods of structural depth detection and detection and evaluation of surface uniformity of exposed rock are designed on the platform of MATLAB programming. The function of GUI is integrated into a graphic interface which is easy to understand and operate, and it is applied to the testing and evaluation of surface quality of EACCP test section in Lidu Town, Fuling District of Chongqing City. The application of digital image technology to the depth measurement of EACCP surface structure, the evaluation of surface distribution uniformity and the adaptability of the program interface are verified.
【學位授予單位】：重慶交通大學
【學位級別】：碩士
【學位授予年份】：2015
【分類號】：U416.216;TP391.41

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本文編號：1645653