100米深孔液壓鉆機變速箱設計
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畢業(yè)設計(論文)任務書
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任務下達日期
設計(論文)開始日期:設計(論文)
完成日期:
一、設計(論文)題目: 100米鉆機變速箱設計
二、專題題目: 軸的機械加工工藝過程
三、設計的目的和意義: 針對傳統(tǒng)鉆探行業(yè)施工過程中設備搬遷困難、鉆孔效率低以及無法傾斜鉆探等問題,研制、改進新一代高效可傾式鉆探設備則尤為必要。該礦用鉆機改型過程中所面對的若干問題進行了較為詳細研究,并對關鍵件加工過程出現(xiàn)的工藝文體進行分析和調整。因此,該設計對改裝其他類型的鉆機具有一定的知道意義。
四、設計(論文)主要內容: 100米鉆機的總體設計、動力的確定、機械傳動系統(tǒng)、變速箱的設計與計算,液壓系統(tǒng)的設計與計算。
五、設計目標: 研制、改進新一代實用的鉆探設備
六、進度計劃:
1.第1~3周 實習、查資料及進行鉆機的結構計算
2.第4~6周 對鉆機的各個部分進行設計計算
3.第7~9周 繪制鉆機總裝圖、速箱組裝圖及零件圖
4.第10~11周。完成專題部分 。
5.第12~13周 完成翻譯部分 第17周準備答辯。
七、參考文獻資料:
1.良貴主編 機械設計 第五版 北京:高等教育出版社 1996
2.俊等主編 機械設計 北京:高等教育出版社,1986
3.章日晉等編 機械零件的結構設計 北京:機械工業(yè)出版社,1987
4.鄭文偉吳克堅主編機械原理第7版北京:高等教育出版社,1997
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附錄1
快速原形機的軟件補償
摘要:這篇論文闡述了快速原形機在參數(shù)誤差成型法和軟件誤差補償方面的改進。這種方法得到多年來在坐標測量機和機械系統(tǒng)參數(shù)值發(fā)展的技術支持??焖僭螜C所有的誤差結果將被輸入一個實際的參數(shù)誤差模型,普通的實體造型依賴于快速原形機和主要坐標測量機的測量。測量結果用來顯示機械誤差函數(shù)和驅動標準刀具的銼刀的誤差補償,對這個方法進行了三次實驗,結果顯示了它充分改善了標準件的精確度。
前言
快速原形機在刀具和輔助設計制造和隨后產生的商品化技術方面起著重要的作用。今天的工藝方法有許多種,例如:光敏液相固化法、熔絲沉積成型法、噴墨打印法、選區(qū)片層黏結法、選區(qū)激光燒結法。這些添加工藝應用范圍很廣。如:概念成型技術,新產品開發(fā)、快速模具制造、生物學。將這種技術發(fā)展成產品技術是一個偶然的機遇,但它已得到了廣泛的應用。但經過CIRP的科學技術委員會調查確認較差的工藝精度,將阻礙技術在機械制造方面的繼續(xù)滲透。
有兩種普通和快速原形一樣可以提高工藝精度。第一種解決這問題的方法是:通過“避免誤差”尋找誤差來源減小誤差。第二種是減小誤差產生的結果,被叫做“誤差補償”。
快速原形技術的研究使誤差避免和原形工藝的許多方面都有所提高。在這些技術中,最受關注的是原形工藝參數(shù)和基本定位完善。因為原形工藝中,有許多工藝變量影響工件的精度,可以完善這些參數(shù)使工件達到最高的精度。復合表面處理技術是典型用來尋工件精度和制造工藝參數(shù)間關系的,一旦獲得復合表面,參數(shù)將控制完成更高的工件精度?;径ㄎ煌晟凭褪且粋€典型的參數(shù)應用和延伸的例子。它被作為一種多元化標準完善問題,控制著表面精度和工件的壽命間的交換。決定變量是工藝參數(shù)設定和工件基本定位。復合表面符合參數(shù)問題是為了使產品優(yōu)化。除了工藝參數(shù)的實體成型和基本定位優(yōu)化,還有原形技術的工藝計劃。如:數(shù)據(jù)文件糾正、切削技術改善、結構傳代、和路線計劃都在進行詳細的研究,目的就是為了工藝改善。
好的工藝計劃,在一定范圍內可以提高機械精度,但是隨著快速原形技術的發(fā)展,即使最好的TUNED系統(tǒng)生產的零件也只是為原形機進行誤差補償。philpott和Gree提出為原形工藝進行反復誤差補償?shù)牟呗?,它補償由于不懂得誤差創(chuàng)造機理而復制積累的誤差。然而因為沒有機械誤差模型建立在這個策略上,所以反復工藝也許對每個新工件進行反復補償。Nee et.al構造了一個矯正的帶有n*n個格子的圖表來提高光敏液相固化工藝精度。這個矯正圖表是根據(jù) 系統(tǒng)的結構來計算的,主要對激光束在平臺上定位的誤差補償。掃描緩沖器和定位標準可以利用這種圖表進行補償。
這篇論文指出多年來CMM誤差參數(shù)值方面的技術發(fā)展使快速原形機的誤差補償更易理解,而且可以用實例參數(shù)誤差進行誤差補償。典型CMM有三個線形托架,設計目的是為惡劣使X、Y、Z軸都獨立移動,然而每個托架有六個自由度,而且硬件結構不能完全消除不必要的移動和轉動。結果每個軸都有三個移動誤差和三個垂直誤差。隨著三個垂直度的增加或軸間的空間誤差增加,一個三軸機器就會有21個參數(shù)誤差,假設此剛體運動,機械的空間誤差能寫出一個有21個參數(shù)的方程,這21個誤差和符號雜表格(1)中有所體現(xiàn)。
在快速原形工藝中,誤差預算除了軸的移動誤差還有許多種,我們的方法是把所有討厭的誤差標成21個實際參數(shù)誤差進行機械容量誤差的全面測量,這有雙重的目的:第一:它將提供一個模型解決補償。第二:它將分離出有意義空間方向上的誤差預算,而且對硬件有一定的診斷作用,同時識別由于其它工藝特征引起的誤差源方向。和CMM、車床不同,快速原形機的21個“實際“參數(shù)不能在機器上直接測量,這個實物成型方法是間接對這些誤差進行測量。也就是說,快速原形機是用來制造特殊設計的實物成型,而CMM具有大規(guī)模測量實物成型的特征,測量是為了推斷快速原形機的參數(shù)誤差,而且誤差補償規(guī)則應用于工件工藝計劃的標準資料
這篇論文的剩余部分是結論,第二部分是解釋SLA機的誤差模型。第三部分介紹三維制圖和參數(shù)誤差方程的起源。第四部分是陳述了理解的方法,測試零件的補償結果。第五部分是總結工作和討論將來的發(fā)展。
2,SLA機的數(shù)學誤差模型
光敏液相固化法是用液態(tài)光敏樹脂做樣品,在一個槽內裝滿光敏液態(tài)聚合物,在下方放有一個升降臺,把沒完成的部分放在樹脂表面下。計算機控制激光通過聚合物表面的方向選擇固化的表層,升降機下降一個距離重新覆蓋一層液態(tài)光敏樹脂,再進行掃描固化,直到全部完畢,SLA250機用在研究層的厚度是0,004。
2.1 SLA機的誤差模型
機械數(shù)學模型根據(jù)機械類型不同實現(xiàn)剛體假設的多樣化。一般來說三軸機器可以根據(jù)探測器的移動和工件分成XYFZ、XYZF、XFYZ或FYXZ幾類,F(xiàn)象征固定機器方程,當其它字母出現(xiàn)在F的右側暗示探測器移動。當字母在F的左側暗示工件移動。
在SLA 250 快速原形機內激光焦點在刀頭上,它由鏡子控制方向,它能移動二個正交水平方向,被分別定義為X、Y。這工作平臺延Z軸帶動工件上下移動,以垂直方向作為Z方向。根據(jù)這些特征SLA 250符合ZFXY典型機。這種類型的快速原形機的分類不能反映快速原形機的實際運動。但是能反映刀頭的運動結果。如:激光焦點。正如我們前面提到的,快速原形機參數(shù)誤差將由生產和測量一個系統(tǒng)部分來確定。而不是測量各個機械軸線移動的精度誤差。這表示機械的實際參數(shù)誤差成型的選擇不代表精度的機械運動學。這就是它與交換方法的不同。每個軸線的六次移動誤差就是以操作運動學鏈的每個同源改變基質。當用實際參數(shù)誤差成型時就必須決定是否這成型能成功地產生補償數(shù)據(jù)來提高機械的精度。討論補償?shù)慕Y果來顯示這成型能提供有用的補償數(shù)據(jù)的能力。
其它原形機也做了同樣的分析,例如:熔司沉積成型機。這刀頭是由X、Y兩個方向移動的托架驅動的。沉積噴頭底座可以沿Z的方向上下移動,因此熔絲沉積成型機也相當于一個ZFYX典型機。圖FIG2是SLA 250機的誤差成型的運動學坐標鏈矢量圖。
用傳統(tǒng)的定義方式,0是坐標原點,X、Y、Z是三個坐標軸,它只包含平移和垂直誤差。在確定運動路線時旋轉誤差被認為獨立存在。T是刀頭在拖架方向的補償。在SLA 250機上沒有真正的X、Y拖架,激光束直接聚焦在刀頭上。因為光束總是聚焦于液體表面,因此SLA 250 機的T=0。一般情況下,T包含在誤差成型的偏差中,但后來被省略了。框格中的W是有原點到激光聚焦點的矢量方向。它代表工件的真實尺寸。運動矢量鏈圖的內容在下面已給出,它們的結果由機械誤差的理論知識是很容易理解的。從原點O到激光焦點有兩條路線:Z——W和X——Y——T。每個運動路線對一個軸線的理論誤差將影響軸線的實際誤差,因此軸線的移動需要根據(jù)理論誤差來修改。X、Y、Z軸的旋轉可由旋轉半徑R(X)、R(Y)、R(Z)表示。讓U代表X、Y、Z,旋轉標量和它們反向公式(2)在圖FIG2中Z和X沒有前身,W有前身軸Z、Y有前身軸X、T有兩個前身軸X和Y。因此這兩個從O到焦點的矢量平衡,可用下面的方程表示(3)。重新整理這方程,矢量W由其它矢量和標量函數(shù)表示(4),用矢量機成型代替X、Y、Z、T、W和旋轉標量。用坐標系統(tǒng)XP、YP、ZP來表示在工件上激光焦點的坐標(5)
TX、TY、TZ是不可重復的誤差,它是由不可重復的內容產生的,因為SLA 250 機沒有刀頭補償如:XT=YT=ZT=0所以數(shù)學模型可簡寫為(6)。EY(X)、EX(Y)、EY(Y)和EZ(Y)都沒有出現(xiàn)在模型中XT=YT=ZT=0就是ZFXY典型機的特征。因為在模型中參數(shù)誤差函數(shù)是實際誤差,因此一些誤差不可能有可理解的物理意思。例如:激光束總是能消除桶表面的樹脂產生正確的誤差、不能表示來自樹脂表面激光束的偏差。
2.2勒讓德多項式約數(shù)
勒讓德多項式可以近似的表示每個參數(shù)誤差函數(shù)。每個平移和旋轉誤差都可以用勒讓德多項式方程的線性來近似表示。例如:是近似的系數(shù),表示第個勒讓德多項式。要得到誤差近似值首先要確定勒讓德多項式的次序,勒讓德多項式的線性連接次序越高,剩余誤差平方的和越小。但是高次序的誤差函數(shù)可以近似制造工藝中的不可重復誤差,促使誤差最后得到補償,在CMM系統(tǒng)中,KRUTH ET。AL指出幾何誤差在系統(tǒng)中會慢慢改變,因此第三順序的勒讓德多項式是好的近似機會。高次序會減少剩余誤差,但會增大不可重復誤差的影響,第三次序的勒讓德多項式在研究中是最接近的。例如:(7)這個方程里有四個未知系數(shù),通過設定絕對零點可使其減少到三個,一般將所有誤差都在軸線的起始點消除。例如:使 和 的關系就可表示為,用代替。則這個方程式就可重新寫為(8)為了方便看,把系數(shù)由代替,同樣表示的系數(shù),表示系數(shù),是軸、的平方誤差。在這樣的定義下,所有的參數(shù)誤差方程都可以用勒讓德方程來表示,但除了直接誤差方程(9)平方誤差和三個直接誤差、、存在一個特殊的關系,簡單說,直接誤差、、的線性關系分別是平方差、、接下來的例子將證實了這點。
找一點P在二維測量機上測量沒有誤差,但在X0、Y0軸間卻有平方誤差,把非正交坐標系中的P點(X0、Y0)可以平移到正交坐標系中用、表示,則(10)得到第一個近似值。這是成立的。因為是非常小是Y0的函數(shù),它是直接誤差##的第一個次序關系式,實際上,直接誤差的線性關系和平方誤差表達的是同一個誤差。它在Y軸的X方向是沒有必要移動的,因為它的大小與Y坐標是成比例的。它是不可能分辨出這兩者,而且用同樣的誤差成型兩次是正確的。在成型中依賴假設事物制造出正交坐標系統(tǒng)是一種方法。早期選擇這種理論這種機械就會被認為是沒有正交坐標系統(tǒng)。因此在成型中包括平方誤差在假設事物下,以上三種直接誤差的線性關系都為零。如:=0,=0, =0或者把機械假設為一個正交坐標系例如:三個軸線彼此是正交的沒有平方誤差存在,但是直接誤差的線性關系最后誤差模型將有同樣的關系量,盡管一個誤差有不同的名字。接下來假設一個正交系統(tǒng),平方誤差將不是單獨成型,在這個假設條件下,在多項式方程中所有的直接誤差都包括線性關系,SLA機成型可被表示為(11)
3.3D 實體造型和參數(shù)誤差方程
3.1 3D實體造型來估計誤差方程系數(shù)
每個誤差方程都需要確定三個系數(shù),因為普通軸正交系統(tǒng)18個參數(shù)誤差的已知系數(shù)的總量為54個,因為SLA 250機正在研究中。因為所以、、不能出現(xiàn)在模型中,因此未知系數(shù)總量變?yōu)?2,至少42個方程能解出所有未知系數(shù),因為不重復誤差的存在,所以確定方程容易一些,靠減少剩余誤差的總量才能解出未知系數(shù)。
用實體造型是零件關鍵特征的表面的位置(x.y.z)在CMM誤差值中,一個高精度的實物造型,如:用不同的定位和方向測量球棒和圓環(huán)來覆蓋,CMM全部的工作容量在快速原形中,快速原形機生產由CMM測量的普通實體造型。假設CMM的精度和重復能力比快速原形機高,用測量的特殊位置來表示誤差模型的函數(shù)去推斷,快速原形機的參數(shù)誤差參數(shù),實體造型的機構不是唯一的,因為它有足夠的不同位置的點提供充足的方程來確定系數(shù)和誤差的最小值。
FIG4展示了這項研究的3D實體造型。它由169個圓柱和13層組成,而且由13個X層和13個Y層交叉形成。通過測量圓柱上表面的中心點可以寫出它的公稱位置和誤差系數(shù)的函數(shù)。圓柱高度排列成一條線,以至于盡可能X、Y、Z結合成獨立的方程。在測量時所有的圓柱表面很容易被CMM探測到,這部分可以提供163*3=507個方程。靠減少不重復誤差來確定42個系數(shù),這些方程是足夠用的。這個實體造型能研究范圍是200*200*100
用缺省的機械系數(shù)可以制定準確的實體造型,這部分可以在平臺中自動制成二次工藝后,3D實體造型在CarlZeiss ECLIPSE 550 CMM機上測量。把一部分坐標系定義為基本表面:X-Y表面,3D實體造型中心作為X、Y的數(shù)據(jù)庫來確定中心點的坐標(X、Y)。
3.2參數(shù)誤差函數(shù)
用一自然非線性程序問題去解算系數(shù),它的目標函數(shù)是縮小剩余非重復性誤差的平方總和。(12)用LinGo編一個優(yōu)化程序可以解出42個系數(shù)。每個多項式誤差函數(shù)的結果在表2中已列出。
三個軸的系數(shù)和參數(shù)誤差函數(shù)已在FIG5中列出,得到以下結論:
1.數(shù)誤差不總是線性函數(shù),也不總是X=0或Y=0對稱的。這表示參數(shù)誤差補償對模型補償是比應用簡單同類收縮率因素補償更精確。
2.在許多多項式中,Z軸的標準誤差,ZTZ是最大的變換誤差,這很容易理解,因為這部分在Z方向上制成一層一層的,這層與上層的連接處會比X、Y方向產生更多的誤差。
4用機械誤差模型進行補償
根據(jù)我們的假設,可以在非補償部分參數(shù)誤差函數(shù),預測點的位置可以提前對部件模型應用補償來提高其精度。預測和補償?shù)慕Y果可以用估算誤差模型的精度。在這部分首先介紹補償?shù)姆椒?,然后介紹他在不同部件上用3D實體造型估算正確的誤差模型方面應用。
4.1當用CAD設計完成原形時,可有好幾種文件格式表示:CAD成型、Pro/E成型、三角測量后的STL文件、二進制格式或AS格式。切削文件由快速原形機的切削軟件制作,闡述誤差補償?shù)哪繕耸怯斜匾???焖僭螜C的誤差模型不是同類時,補償部分的同一多項式當然也將改變,也就是說平面將不是平面,球面將不是球面。假如可能用CAD系統(tǒng)進行補償,但也是很難的,因此用CAD模型補償是不實際的。STL文件在快速原形工業(yè)中是defacto格式,應用在快速原形工藝上有兩種典型的格式:二進制文件和ASC11文件、二進制格式很常用,因為容量小,但它的格式沒有ASC11格式易讀易改。另一方面ASC11 STL文件有以下格式:
除了第一行和最后一行,這文件可以分為幾個小單元,每七行一個單元,每個單元都是以facet normal 開始以 end facet結束。每個單元都由記錄的三個垂直度的坐標來描述一個面,每個面是一個普通的單元矢量。在FIG6有一個圓柱,在兩個圓環(huán)邊界上有三條線相互垂直,補償可以應用在這些邊界環(huán)的垂直點上,這暗示了當創(chuàng)造層建立部件的標準工藝時,圓柱體只能接受來自上下底面邊界移位留下的補償,這是粗糙補償,另一個精致補償代替了每層的輪廓線或切片。當STL文件成為切片后,被顯示在FIG7中,每個輪廓由線組成,最后連成環(huán)成為層的邊界,而且在層形成時建立了標準刀具。對切片進行補償,其補償方法和機械分層方法效果是一樣的,然而切片格式有時是專用的,而且不易理解的。ASC11 STL文件應用誤差補償更容易被接受,并且得以證實。
假設一機械誤差模型在STL文件中每個頂點的實際位置都可被預測實現(xiàn)位置和虛擬位置間的誤差可以補償。相反,意義不同的是提前STL文件中添加虛擬頂點的坐標,每個單元矢量要用補償垂直度為每個面進行反復計算。一個FORTRAN程序可以對STL文件進行系統(tǒng)的修改。
下面這段是用補償程序提高三個不同例子部件的精度,為了證明補償程序對提高特殊位置精度,側面精度和厚度精度的能力。
4.2用補償來提高特殊位置的精度
設計一個部件與3D實體造型相似的幾何圖形拉進行研究,這部件有49個直徑相同的圓柱,但位置無序而且高度不同,用同一個SLA機和一樣的參數(shù)背景復制了兩個部件,但一個用補償、一個沒有補償。容量誤差如:計算每個圓柱上表面中心的實際位置和虛擬位置的距離,并且作為誤差圖繪制如圖FIG8數(shù)據(jù)顯示,在補償部分的容量誤差急劇下降。
計算誤差減少量,計算每點補償后的容量和補償前的容量誤差比率。49個點的比率的一部分繪制在圖FIG9中。平均容量誤差比原來的值減少大約30%,這意味著誤差補償后實際點與虛擬位置更接近。然而由于在快速原形工藝中無重要重復因素,并且Z值量是分層制造使Z方向誤差增大。所以說這比率與統(tǒng)計分配有關。大部分數(shù)據(jù)下降在10——60%之間,當一個點的數(shù)值降副大于1,則Z值將由下段來闡述。
4.3用補償來提高側面精度
在前面已經證明補償可以提高個別點的位置精度,在這段設計了一個半徑為45.72mm的半圓形去研究怎樣的補償才能提高連續(xù)表面?zhèn)让娴木?,如圖FIG10在半圓形表面選擇90個點進行測量,這些點覆蓋半圓表面,它可以靠減小偏差的平方總數(shù)來確定一個完美的球面。在這些點中有一個最大偏差值和最小偏差值點,這兩個點可以確定兩個同心圓,所有的餓點都包括在內,用這兩個同心圓的范圍作為這表面的餓側面精度的近似值。在表3中列出了補償前和補償后的計算結果。
附錄2
Software compensation of rapid prototyping machines
Kun Tong, E. Amine Lehtihet, Sanjay Joshi
The Harold and Marcus Department of Industrial and Manufacturing Engineering, The Pennsylvania State University,358 Leonhard Building, University Park, PA 16802, USA Received 22 January 2003 ; received in revised form 6 October 2003 ;accepted 6 November 2003.
Abstract:This paper addresses accuracy improvement of rapid prototyping (RP) machines by parametric error modeling and software error compensation. This approach is inspired by the techniques developed over the years for the parametric evaluation of coordinate measuring machines (CMM) and machine tool systems. The confounded effects of all errors in a RP machine are mapped into a “virtual” parametric machine error model. A generic artifact is built on the RP machine and measured by a master CMM. Measurement results are then used to develop a machine error function and error compensation is applied to the files which drive the build tool. The method is applied to three test parts and the results show a significant improvement in dimensional accuracy of built parts.
Keywords: Rapid prototyping; Parametric modeling; Software error compensation; STL files
1. Introduction
Rapid prototyping (RP) machines are now an important part of the vast array of tools and techniques used to assist in the design, manufacture and subsequent commercialization of a product [1,2]. Today’s commercial machines offer a variety of processes such as the stereo lithography apparatus (SLA), fused deposition modeling (FDM), ink jet printing (IJP), laminated object manufacturing (LOM) and selective laser sintering (SLS). These additive processes are used in a wide range of applications such as concept modeling, new product marketing, rapid tooling, and biomedical. Many of the challenges encountered to develop this technology into a production technique with a wide range of applications have been overcome. However, the survey by the CIRP’s Scientific Technical Committee [3] identifies the inferior dimensional accuracy of these processes as the one remaining obstacle which prevents this technology from greater penetration of manufacturing activities. There are two general approaches which can be used to improve the accuracy of a process such as RP. The first approach attacks the problem through “error avoidance” and seeks to eliminate the source of an error. The second approach strives to cancel the effect of an error without removing the error source and is known as “error compensation” [4–6].
Most studies on RP accuracy improvement to date fall within the error avoidance category and have focused on different aspects of the RP process. Among these, RP process parameters tuning [7–10] and build orientation optimization [11–14] have drawn the most attention. For any RP process, there are many process variables that affect part accuracy. The setting of these parameters could be optimized to achieve the best part accuracy. Response surface methodology (RSM) is typically used to find the relationship between part accuracy and manufacturing process parameters [8]. Once a response surface is obtained, parametric tuning is then conducted to achieve better part accuracy. Optimization of build orientation is a typical example of an application and extension of parameter tuning. It is usually formulated as a multi-criteria optimization problem, managing the trade off between surface finish, part accuracy and part build time. Decision variables are the process parameter settings and part building orientation. Response surfaces fitted in parameter tuning problem are then used in optimization. Besides process parameters tuning and build orientation optimization, other aspects of process planning of RP techniques such as data file correction, slicing technique improvement, support structure generation and path planning have also been studied in detail for process improvement [15–20]. Good process planning can improve machine accuracy to some extent, but with the current RP technology, even the best tuned system will still produce parts with considerable systematic errors. Error compensation can be used to further reduce errors. However, very little work, if any, has been done on error compensation for RP machines. Philpott and Green [21] present an iterative error compensation strategy for one RP process, which compensates for cumulative error build-up during replication without knowledge of the error creating mechanism. However, since no machine error models were built in this strategy, the iterative process needs to be repeated for every new part. Nee et al. [14] constructed a correction table with n × n lattice points to improve the stereo lithography process accuracy. This correction table is calculated according to the configuration of the Galvano-mirror system and is used mainly to compensate for the error in positioning the laser beam on the platform. This table is uploaded to the scanner buffer and positioning values are compensated by values in the table. This paper presents a more comprehensive method for RP machines error evaluation and error compensation using” virtual ” parametric errors, inspired by the technique developed over the years for parametric evaluation of CMM errors [4–6,22–29]. A typical CMM has three linear carriages, designed to move independently along X, Y,or Z axis. How- ever, each carriage has six degrees of freedom and hardware construction usually cannot completely suppress the undesired translational or rotational movement. As a result, each axis has three translational errors and three rotational errors. With the addition of three perpendicularity or squareness errors between the axes, a three-axis machine has a total of 21 parametric errors [4–6,23,27]. Assuming rigid body kinematics, the volumetric error of the machine can be written as a function of the 21 parametric errors. These 21 errors and the notation used for representation are summarized in Table 1.
In the RP processes, the error budget is quite large and includes many items other than axes motion errors [30–32]. Our approach is to map all these confounded errors into 21“virtual” parametric errors as a global measure of machine volumetric accuracy. This will serve a dual purpose: first, it will provide a model with sufficient resolution for compensation; second, it will partition the error budget along meaningful spatial directions and serve as a diagnostic tool for intervention on the hardware (drives, controller) as well as a diagnostic tool for the identification of direction dependent error sources due to other process characteristics. Unlike the case of CMM’s and machine tools, the 21 “virtual” parametric errors of a RP machine cannot be measured directly on the machine, and the artifact method is thus used for an indirect measurement of these errors. That is, the RP machine is used to manufacture a specially designed artifact, and a CMM is used as a master scale to measure artifact characteristics. Measurements are then used to infer the parametric errors of the RP machine, and an error compensation routine can then be applied to the build files of any part scheduled for processing by the machine. The rest of the paper is organized as follows. Section 2 explains the SLA machine error model. Section 3 introduces the 3D artifact and the parametric error functions derived from it. Section 4 presents the compensation method, test parts compensation results and Section 5 summarizes the work and discusses possible future work.
2. Mathematical error model of SLA machine
Stereo lithography apparatus (SLA) creates a prototype by photo curing a liquid resin. A vat is filled with photo-curable liquid polymer with an elevator platform carrying the unfinished part set below the surface of the resin. The computer controlled optical scanning system directs a laser beam across the top of the polymer, which selectively hardens the surface layer. The machine then lowers slightly to cover the top surface of the unfinished part with another layer of the liquid resin, continuing to harden layer by layer until the complete part is built. Layer thickness of the SLA 250 machines used in this study is set to 0.004 in. (0.1016 mm) (Fig. 1).
2.1. SLA machine error model
Mathematical models of machines based on rigid body assumptions vary according to machine types. In general, three-axes machines can be classified according to the motion of the probe and work piece as XYFZ, XYZF, XFYZ or FYXZ. In this representation, F designates the fixed machine Twenty-one parametric errors of a three axes system foundation while letters appearing to the right of F indicate work piece motion [23]
In the SLA 250 rapid prototyping machine, the focus of the laser beam corresponds to the tool tip in machine tools. It is directed by mirrors and can move in two orthogonal horizontal directions, which are defined as X and Y, respectively. The work platform carrying the work piece can move up and down along the Z-axis, with the vertical up as positive Z-direction. According to these features, SLA 250 corresponds to a ZFXY type machine. This classification of the RP machine type does not reflect the actual kinematics of the RP machine, but reflects the resulting motion of the tool tip, i.e., the laser focus in this case. As mentioned previously, the RP machine parametric errors will be determined by producing and measuring282 b
Fig. 1. The SLA machine.
an artifact part, rather than measuring the actual error of the motions of the individual axis of the machine. This allows for the selection of a “virtual” parametric error model of the machine which does not represent the actual machine kinematics. This is different from the traditional approach where the six error motions of each axis are directly measured to populate the individual homogeneous transformation matrices in the kinematics chain. When using “virtual” parametric error model, it has to be determined if the model can successfully produce compensation data to improve the machine accuracy. Compensation results discussed later in the paper will demonstrate the ability of this model to provide useful compensation data.
The same analysis can be applied to other RP machines. For example, in a FDM machine, the tool tip is a deposition nozzle driven by two carriages in X and Y directions and the table moves up and down in Z direction. A FDM machine thus corresponds to a ZFYX type machine. The kinematic axes chain vector diagram in Fig. 2 is used to build the error model for SLA 250.
Fig.2.The SLA250 machine axes chain vector diagram.
Under the conventional definition method [29,33],O is the fixed origin. X, Y and Z are the three axes vectors, including only the translational and squareness errors. The rotational errors will be considered separately later when writing the kinematical paths. T is the tool tip offsets xt , yt and zt with respect to the carriage to which the tool is attached. In the SLA 250 machine, there are no real X and Y carriages and the laser beam focus itself is considered the tool tip. Since the beam focus is always on the liquid surface, thus for the SLA 250 machine T = 0. For generality, T will be included in the error model derivations but dropped afterwards. W is the vector directed from the part origin to the laser focus in the part frame, which represents the actual size of the part. The components of the kinematical vector chain diagram are given below. Their structure is easily understood by rationalizing the effects of the machine errors on positioning ability [29]:
(1)
There are two kinematic paths from origin O to laser beam focus: Z → W and X → Y → T. In each kinematic path, the rotational error of the predecessors to an axis will affect the actual movement of that axis, thus the axis movement needs to be modified by the rotational error of its predecessors. Rotation of X, Y and Z axes can be represented by infinitesimal rotation matrices R(X), R(Y), and R (Z). Letting u represent X,Y or Z, the rotation matrix and its inverse are respectively:
There are two kinematic paths from origin O to laser beam focus: Z → W and X → Y → T. In each kinematic path, the rotational error of the predecessors to an axis will affect the actual movement of that axis, thus the axis movement needs to be modified by the rotational error of its predecessors. Rotation of X, Y and Z axes can be represented by infinitesimal rotation matrices R(X), R(Y), and R(Z). Letting u epresent X,Y or Z, the rotation matrix and its inverse are respectively:
In Fig. 2, Z and X have no predecessor. W has a predecessor axis Z, Y has a predecessor axis X, and T has two predecessor axes: X and Y. Thus, the two equivalent vector chains from origin O to laser beam focus can be expressed by the following equation:
After rearranging the terms, vector W is explicitly written as a function of all other vectors and matrices:
Substituting X, Y, Z, T, W and rotational matrixes into the vector machine model, the expressions for the coordinates of the laser focus in the work piece coordinates s
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