【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(duì)汽車尾氣排放的要求越加嚴(yán)格,也使車企更加關(guān)注汽車的經(jīng)濟(jì)性和排放性,而對(duì)燃油噴霧特性進(jìn)行深入研究對(duì)發(fā)動(dòng)機(jī)燃油經(jīng)濟(jì)性及排放性有著重要的意義。本文提出在對(duì)噴霧圖像進(jìn)行處理的過程中,將圖像中的粒子提取出來,并建立和擴(kuò)充相應(yīng)的粒子庫。在MATLAB/GUI平臺(tái)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(jìn)行連接。將發(fā)動(dòng)機(jī)噴霧實(shí)驗(yàn)獲取的噴霧圖像導(dǎo)入噴霧圖像粒子庫管理系統(tǒng)中,使用區(qū)域生長算法對(duì)閾值處理后的圖像進(jìn)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(duì)閾值處理后的圖像進(jìn)行匹配,使用區(qū)域生長算法對(duì)未匹配成功的新粒子進(jìn)行信息提取,并將新的粒子添加到相應(yīng)的粒子庫中,完成粒子庫的擴(kuò)充。通過改進(jìn)的SSDA算法與NCC算法的融合,得到一種新的匹配算法進(jìn)行圖像匹配。本文用Photoshop畫出仿真粒子圖像,并將圖像導(dǎo)入噴霧圖像粒子庫管理系統(tǒng)中,對(duì)噴霧圖像粒子庫管理系統(tǒng)進(jìn)行調(diào)試,其運(yùn)行結(jié)果驗(yàn)證了噴霧圖像粒子庫管理系統(tǒng)的實(shí)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(dǎo)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(duì)該工況的粒子庫進(jìn)行了擴(kuò)充,并統(tǒng)計(jì)出圖像(a)和圖像(b)中不同長短軸粒子的個(gè)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(xué)位授予單位】：長安大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2016
【分類號(hào)】：U464

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