本文選題：鈦合金葉片 + 銑削加工�。� 參考：《南京航空航天大學(xué)》2017年碩士論文

【摘要】：鈦合金具有比強(qiáng)度高、耐高溫、耐腐蝕等優(yōu)良特性,在國(guó)防工業(yè)和民用航空領(lǐng)域得到了廣泛的應(yīng)用,特別是在航空航天發(fā)動(dòng)機(jī)的應(yīng)用上極為廣泛。同時(shí),鈦合金的優(yōu)良特性也使其成為了典型的難加工材料。鈦合金在加工過(guò)程中,容易產(chǎn)生嚴(yán)重的刀具磨損,從而影響加工表面質(zhì)量及加工效率,甚至?xí)疠^高的廢品率。本文為提高鈦合金葉片加工過(guò)程中刀具磨損及工件表面粗糙度測(cè)量的便利性,開(kāi)展基于視覺(jué)的便攜式測(cè)量技術(shù)研究,為鈦合金葉片加工提供方便可行的過(guò)程監(jiān)測(cè)方法。所完成的主要研究?jī)?nèi)容及取得的成果如下:(1)開(kāi)展了刀具磨損便攜式在位檢測(cè)技術(shù)研究。對(duì)比分析了現(xiàn)階段刀具磨損檢測(cè)技術(shù)及優(yōu)缺點(diǎn),結(jié)合加工現(xiàn)場(chǎng)的要求,提出了一種便攜式刀具磨損在位檢測(cè)方法。該方法通過(guò)將微型顯微鏡夾持于手機(jī)攝像頭上,可對(duì)刀具磨損圖像進(jìn)行拍攝。然后將磨損圖像傳入計(jì)算機(jī)中,通過(guò)圖像處理與數(shù)據(jù)分析,便可獲得刀具磨損量。通過(guò)誤差分析,驗(yàn)證了該方法的有效性。由于測(cè)量時(shí)不用卸下刀具,所以該方法顯著縮短了刀具磨損的檢測(cè)時(shí)間,并且與常規(guī)離線測(cè)量方法相比,無(wú)需重新對(duì)刀。(2)采用視覺(jué)檢測(cè)方法,研究了銑削參數(shù)對(duì)刀具磨損的影響規(guī)律。設(shè)計(jì)了鈦合金TC4的正交銑削實(shí)驗(yàn),結(jié)合鈦合金葉片實(shí)際加工需求,系統(tǒng)研究了銑削速度、每齒進(jìn)給量和銑削寬度對(duì)硬質(zhì)合金刀具耐用度的影響規(guī)律。研究發(fā)現(xiàn),刀具在使用初期和后期的磨損比較嚴(yán)重,中期時(shí)比較平穩(wěn);獲得了銑削參數(shù)對(duì)刀具磨損的影響規(guī)律。在實(shí)驗(yàn)數(shù)據(jù)的基礎(chǔ)上,建立了刀具耐用度的經(jīng)驗(yàn)預(yù)報(bào)模型。(3)研究了鈦合金加工表面粗糙度Ra及其與圖像特征間的關(guān)系。首先,采用觸針式粗糙度儀對(duì)已加工表面粗糙度進(jìn)行了測(cè)量分析,通過(guò)單因素實(shí)驗(yàn),獲得了冷卻條件、銑削參數(shù)等對(duì)表面粗糙度的影響趨勢(shì)。在此基礎(chǔ)上,應(yīng)用所提出的視覺(jué)測(cè)量方法,對(duì)加工試件的表面圖像特征開(kāi)展了研究,分析了直方圖標(biāo)準(zhǔn)差與粗糙度之間的關(guān)系。研究表明,兩者之間具有良好的相關(guān)性,所提出的視覺(jué)方法可用于實(shí)際加工過(guò)程中工件表面粗糙度的監(jiān)測(cè)。
[Abstract]:Titanium alloys with high specific strength, high temperature resistance and corrosion resistance have been widely used in the field of national defense industry and civil aviation, especially in aerospace engines. At the same time, titanium alloy has become a typical refractory material because of its excellent properties. In the process of machining titanium alloy is easy to produce serious tool wear which will affect the quality and efficiency of machining surface and even lead to higher scrap rate. In order to improve the convenience of tool wear and measurement of workpiece surface roughness during the machining of titanium alloy blade, the portable measurement technology based on vision is studied in this paper, which provides a convenient and feasible process monitoring method for titanium alloy blade machining. The main research contents and achievements are as follows: 1. This paper compares and analyzes the present tool wear detection technology and its merits and demerits, and puts forward a portable tool wear in-situ detection method combined with the requirements of machining field. The tool wear image can be photographed by holding the micro microscope on the camera of the mobile phone. Then the wear image is introduced into the computer and the tool wear can be obtained by image processing and data analysis. The effectiveness of the method is verified by error analysis. Because the tool is not removed when measuring, this method can significantly shorten the testing time of tool wear, and compared with the conventional off-line measurement method, there is no need to rematch the tool. The influence of milling parameters on tool wear was studied. The orthogonal milling experiment of titanium alloy TC4 was designed. The effects of milling speed, feed per tooth and milling width on the durability of cemented carbide cutting tools were systematically studied according to the actual machining requirements of titanium alloy blades. It is found that the wear of the tool is more serious in the early and late stage of use and stable in the middle stage, and the influence of milling parameters on tool wear is obtained. Based on the experimental data, an empirical prediction model of tool life is established. The relationship between surface roughness Ra and image characteristics of titanium alloy machining is studied. Firstly, the roughness of machined surface is measured and analyzed by using a touch needle roughness instrument. The influence trend of cooling conditions and milling parameters on the surface roughness is obtained by single factor experiment. On this basis, the surface image features of processed samples are studied by using the proposed visual measurement method, and the relationship between histogram standard deviation and roughness is analyzed. The results show that there is a good correlation between the two methods, and the proposed visual method can be used to monitor the surface roughness of workpiece in the process of practical machining.
【學(xué)位授予單位】：南京航空航天大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TG54

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