【摘要】：隨著石油資源的日益枯竭和世界范圍內(nèi)空氣污染的加劇,致使各國對汽車尾氣排放的要求越加嚴格,也使車企更加關(guān)注汽車的經(jīng)濟性和排放性,而對燃油噴霧特性進行深入研究對發(fā)動機燃油經(jīng)濟性及排放性有著重要的意義。本文提出在對噴霧圖像進行處理的過程中,將圖像中的粒子提取出來,并建立和擴充相應的粒子庫。在MATLAB/GUI平臺上開發(fā)燃油噴霧圖像粒子庫管理系統(tǒng),并將該管理系統(tǒng)與SQL Server粒子數(shù)據(jù)庫進行連接。將發(fā)動機噴霧實驗獲取的噴霧圖像導入噴霧圖像粒子庫管理系統(tǒng)中,使用區(qū)域生長算法對閾值處理后的圖像進行粒子信息提取,并將提取的粒子添加到粒子庫中,完成粒子庫的生成。調(diào)用粒子庫中的粒子對閾值處理后的圖像進行匹配,使用區(qū)域生長算法對未匹配成功的新粒子進行信息提取,并將新的粒子添加到相應的粒子庫中,完成粒子庫的擴充。通過改進的SSDA算法與NCC算法的融合,得到一種新的匹配算法進行圖像匹配。本文用Photoshop畫出仿真粒子圖像,并將圖像導入噴霧圖像粒子庫管理系統(tǒng)中,對噴霧圖像粒子庫管理系統(tǒng)進行調(diào)試,其運行結(jié)果驗證了噴霧圖像粒子庫管理系統(tǒng)的實用性。將噴嘴孔徑為0.366 mm,噴油壓力為20Mpa工況下的兩張較清晰的噴霧圖像(a)和噴霧圖像(b)分別導入粒子庫管理系統(tǒng)中,圖像(a)生成了該工況的粒子庫,圖像(b)對該工況的粒子庫進行了擴充,并統(tǒng)計出圖像(a)和圖像(b)中不同長短軸粒子的個數(shù)。
[Abstract]:With the increasing depletion of oil resources and the intensification of air pollution in the world, the requirements of automobile exhaust emissions become more stringent in various countries, and the automobile enterprises pay more attention to the economy and emissions of cars. The research on fuel spray characteristics is of great significance to engine fuel economy and emission. In this paper, in the process of spray image processing, the particles in the image are extracted, and the corresponding particle library is established and expanded. A fuel spray image particle library management system is developed on MATLAB/GUI platform, and the system is connected to the SQL Server particle database. The spray image obtained from engine spray experiment is imported into the particle library management system of spray image, and the particle information is extracted from the image after threshold processing by using the region growth algorithm, and the extracted particles are added to the particle library. Complete the generation of particle library. The particles in the particle library are called to match the image after threshold processing, and the region growth algorithm is used to extract the information of the new particle that has not been matched successfully, and the new particle is added to the corresponding particle library to complete the expansion of the particle library. Through the fusion of improved SSDA algorithm and NCC algorithm, a new matching algorithm for image matching is obtained. In this paper, Photoshop is used to draw the simulated particle image, and the image is imported into the spray image particle library management system, and the system is debugged. The running results verify the practicability of the spray image particle library management system. Two clear spray images (a) and (b) with a nozzle aperture of 0.366 mm, injection pressure of 20Mpa were imported into the particle library management system respectively. The image (a) generated the particle library of the working condition. Image (b) extends the particle library of this working condition and calculates the number of particles in image (a) and image (b) with different long and short axes.
【學位授予單位】：長安大學
【學位級別】：碩士
【學位授予年份】：2016
【分類號】：U464

【參考文獻】

相關(guān)期刊論文 前10條

1 曹建明;;射流表面波理論的研究進展[J];新能源進展;2014年03期

2 劉穎;;計算機圖像識別技術(shù)的發(fā)展現(xiàn)狀與展望[J];考試周刊;2014年08期

3 竇華軍;;基于數(shù)字圖像處理技術(shù)分析[J];數(shù)字技術(shù)與應用;2013年12期

4 聶歡歡;伊磊;劉任平;;基于區(qū)域生長法提取二值圖像中的連通區(qū)域[J];計算機時代;2012年06期

5 陳露晨;李光明;;快速最大熵多閾值圖像分割算法[J];計算機應用與軟件;2012年03期

6 汪丹平;唐勇;;基于直方圖的迭代式自動閾值分割技術(shù)研究[J];軟件導刊;2011年08期

7 李賢華;彭真;;基于JDBC-ODBC的數(shù)據(jù)庫訪問方法的設(shè)計與實現(xiàn)[J];計算機與現(xiàn)代化;2008年05期

8 孫卜郊;周東華;;基于NCC的快速匹配算法[J];傳感器與微系統(tǒng);2007年09期

9 張杰;張蕊蕊;胡卜元;白素芳;徐璇;;煤焦SEM圖像的表面孔洞分形維數(shù)的Matlab實現(xiàn)[J];河北工程大學學報(自然科學版);2007年02期

10 曹建明;噴霧學研究的國際進展[J];長安大學學報(自然科學版);2005年01期

，

本文編號：2297389