智能機床外文翻譯

1、畢業(yè)設計中英文 翻譯 學生姓名： 學號： 學 院： 專 業(yè)：機械設計制造及其自動化 指導教師： 2013年5 月 原文： 48.4.4 Autonomous and Intelligent Machine Tool The whole machining operation of conventional CNC machine tools is predetermined by NC programs. Once the cutting conditions, such as depth of cut and stepover, are given by the machi ning com

2、ma nds in the NC programs, they are not gen erally allowed to be cha nged duri ng machining operations. Therefore NC programs must be adequately prepared and verified in adva nee, which requires exte nsive amounts of time and effort. Moreover, NC programs with fixed comma nds are not resp on sive to

3、 un predictable cha nges, such as job delay, job insertion, and mach ine breakdow n found on mach ining shop floors. Shirase proposed a new architecture to con trol the cutt ing process aut onom ously without NC programs. Figure 48.29 shows the conceptual structure of autonomous and intelligent mach

4、ine tools (AIMac). AIMac con sists of four functional modules called man ageme nt, strategy, predict ion, and observation. All functional modules are connected with each other to share cutting in formatio n. noi kpivce nhodul/C AD data Process OP 2 Pticka M/fhinmg sequence Tl Stratum Cw/ring conditi

5、on Lkfpth of cm Slepciver Feed rate Spi ndle s-pecd llk為i卿 Prediction Process Machining status M配hining trouble (ch oiler v i hmiiunB lool hreaksiprlL g Culling comihifflii Machining kflH.MIXTTA Obsciviilioti ffiT血臨陽 Mt hiiljc tod daU Tbd data Real time jBrwm stimulating MacJiining pmcc航 Cutting for

6、ce M juhiiiuig crux Chatter ldhratinn Cutting lernperaliiire Tool wear, 血- liol path CL data Rtdl machining Fig. 48.29 Con ceptual structure of AIMac 科科itnrin靈 Feed rale Spindk speed Spi nd I l! ltLid Cutling force Vibraiion TcmpcraLun： Tool wear. etc. Digital Copy Milli ng for Real-Time Tool-Path G

7、en eratio n A tech nique called digital copy milli ng has bee n developed to con trol a CNC machi ne tool directly. The digital copy milli ng system can gen erate tool paths in real time based on the prin ciple of traditional copy milling. In digital copy milling, a tracing probe and a master model

8、in traditional copy milling are represented by three-dimensional (3-D) virtual models in a computer. A virtual tracing probe is simulated to follow a virtual master model, and cutter locations are gen erated dyn amically accord ing to the moti on of the virtual trac ing probe in real time. In the di

9、gital copy milli ng, cutter locati ons are gen erated aut onom ously, and an NC mach ine tool can be in structed to perform milli ng operati on without NC programs. Additi on ally, not only stepover, but also radial and axial depths of cut can be modified, as shown in Fig. 48.30. Also, digital copy

10、milli ng can gen erate new tool paths to avoid cutti ng problems and cha nge the mach ining seque nee during operatio n 48.12. Furthermore, the capability for in-process cutti ng parameters modificati on was dem on strated, as show n in Fig. 48.31 48.13. Real-time tool-path gen eratio n and the moni

11、 tored actual milli ng are shown in the lowerleft corner and the upper-right corner of this figure. The monitored cutting torque, adapted feed rate, and radial and axial depths of cut are show n in the lowerright corner of this figure. The cutting parameters can be modified dynamically to maintain t

12、he cutting load. a)b) Fig. 48.30a d Example of real-time tool-path gen erati on. (a) Bilateral zigzag paths; (b) contouring paths; (c) change of stepover; (d) change of cutting depth Fig. 48.31 Adaptive milli ng on AIMac Rure mill 080 mm Sc aim incline mode End mill.0 10mm Conlour-line arode End) mi

13、l0 16mm Sranniog-line mode End mill O lOnun Scanning-line mode S = 1000 rpm F= IJO-nniinjio RD = S mm AD = 5 mm S = 2450 rpm. F = 346 mm/mju RD= 1.6mm.AD =38 mm S= IGSOrpra-F = 24 iromZniiin RD = 4.5 nrm_ AD = 2.1 mm 5 = 2450 rprnn F= 346 rnm/niiji RD = L6 min, 4 = 3.& mra 1 Open pocket 3 Closed doL

14、 * 4 End mill 0 10 mm Scann incline mode End) mil l 0 6 imi Scanning-line mode End mill 06 mm Scanning-line mode Ball end mill 0 10 mm Sannis-血 n血 5 = 2450 rpm F = 346 nimJiniri RD = 1.6 mm. AD=3_8 jtutl S = 3539 irpm. F = 413 RD= lJ2inm.AD = 2.l mm S = 3539 rpra. F=413 inniAmiin. RD = 12. jthtl AD

15、= 2.1 mm 5 = 2580 iprOr F= 335 ram/miji RD = l3imAD = 3.2 mra Closed slot- s 1 5 Closed F6 Open slot 7 Free form 8 drill 03 mm Drill 誕 OKxte Drill 010 mm Drill ng mode Raw malerial shape Finished shape 3 = 154 rpm. F = 232 nrnvkiki S = S4fi rpnL F = 1-80 nun/mi口 Blind bole Blind hole 目ji Fig. 48.32

16、Results of mach ining process pla nning on AIMac Flexible Process and Operati on Planning System A flexible process and operati on pla nning system has bee n developed to gen erate cutti ng parameters dyn amically for mach ining operati on. The system can gen erate the product ion pla n from the tot

17、al removal volume (TRV). The TRV is extracted from the in itial and fini shed shapes of the product and is divided into mach ining primitives or mach ining features. The flexible process and operati on pla nning system can gen erate cutt ing parameters accord ing to the machi ning features detected.

18、 Figure 48.32 shows the operatio n seque nee and cutt ing tools to be used. Cutt ing parameters are determ ined for the experime ntal machi ning shape. The digital copy milli ng system can gen erate the tool paths or CL data dyn amically accord ing to these results and perform the aut onom ous milli

19、 ng operati on without requiri ng any NC program. 48.5 Key Technologies for Future Intelligent Machine Tool Several architectures and tech no logies have bee n proposed and in vestigated as men ti oned in the previous sect ions. However, they are not yet mature eno ugh to be widely applied in practi

20、ce, and the achieveme nts of these tech no logies are limited to specific cases. Achieveme nts of key tech no logies for future in tellige nt mach ine tools are summarized in Fig. 48.33. Process and mach ining quality con trol will become more importa nt tha n adaptive con trol. Dyn amic toolpath ge

21、neration and in-process cutting parameters modification are required to realize flexible mach ining operati on for process and mach ining quality con trol. Additi on ally, in tellige nt process monitoring is needed to evaluate the cutting process and machining quality for process and mach ining qual

22、ity con trol. A reas on able strategy to con trol the cutt ing process and a reas on able in dex to evaluate machi ning quality are required. It is therefore n ecessary to con sider utilizati on and learning of knowledge, knowhow, and skill regarding machining Operations. A process pla nning strateg

23、y with which one can gen erate flexible and adaptive work ing pla ns is required. An operati on pla nning strategy is also required to determ ine the cutt ing tool and parameters. Product data an alysis and machi ning feature recog niti on are importa nt issues in order to gen erate operati on pla n

24、s aut onom ously. Sections 48.4.2 - 48.5 are quoted from 48.14. CcnccpIiiiiL Confirmed Practical Motion control Adaptive control Process Lind quality conirol : Fhf iirii tfkri ifliJ （囂戶il 船陸n I LTimUIVI Intelligent process monitoring A Open Hixhileclure toncept Process planning Operation planning Ul

25、ilization of tnewhow Lemming of knowhow Network communication Distributed coinpuling Fig. 48.33 Achieveme nts of key tech no logies for future in tellige nt mach ine tools 譯文： 4844智能機床 整個傳統(tǒng)數(shù)控機床的機械加工是在預定的數(shù)控程序下進行的。一旦切削條件 （如切削深度和進給量）在數(shù)控程序指令中被指定，在機械加工操作中，他們一 般不允許被改變。因此，數(shù)控程序必須有大量的時間和精力用來提前準備和驗證。 此外，基于固定命

26、令的數(shù)控程序在遇到不可預知的變化時不會響應，比如工作延 遲和加工車間中的機器故障。 Shirase提出了一種新的結構在沒有數(shù)控程序的情況下可以自動控制切削 過程。圖48.29顯示了智能機床概念結構。AIMAC包括四個功能模塊稱為管理、 策略、預測和觀察。所有功能模塊都與彼此分享切削信息。 Wciritplwv! modrl/CAO data IRiaw rrateriad %isinugunent Resource l3tedki|on Obsen ation Process difljr刖打 t Etepth of cot Stepover Feed mtc Spindle speed Ma

27、chining knowhow Mzichiikj 11x)1. dl j Tool data Jesounre and Reul time process stimulation hi 肚hi ru血g pftxx 沾 Cullinc force Machin-im error Chsallcr vihohwi Cutting EirmpraLmn! Tool wear etc. T2T3 PlanningMachimtig seqijence Pfuca Tool ll ft l-IU-C I-1 PT2L,T5 Machinirig 伽lurv Cutiing eondidon tfr/

28、lrrufiitin Cutting am曲祜尺 mainlmact Machining sutus Machiining tfoubl e (chatter vibraticifi. tiMil hrviiliw), elc. Feedale Spindle speed Spindlc load futhng loftt! Wiralion Tempera lunr Toni 謝cm. clc. MM 圖48.29 AIMac的概念結構 數(shù)字仿形銑削-對刀具軌跡進行實時生成 數(shù)字仿形銑削技術被研發(fā)出來后，它可以直接控制數(shù)控機床。數(shù)字仿形銑削 系統(tǒng)可以根據(jù)系統(tǒng)的仿形銑削及時生成刀具路徑。在數(shù)字

29、仿形銑削中，傳統(tǒng)仿形 銑削中的跟蹤探測器和主模型通過計算機用三維虛擬模型表現(xiàn)出來。虛擬跟蹤探 測器模擬虛擬主模型，根據(jù)動態(tài)的虛擬軌跡實時生成刀具坐標。在數(shù)字仿形銑削 中，刀具坐標可自主生成，數(shù)控機床可以在沒有數(shù)控程序情況下可以按指示執(zhí)行 銑削操作。此外，不僅是行距，而且徑向和軸向切削深度也可以修改（見圖 48.30 ）。同時，數(shù)字仿形銑削可以生成新的刀具路徑，以避免切削問題和改變操 作工程中的加工順序48.12。 此外，對于切割過程中的參數(shù)修改能力也得到了證實，如圖48.3148.13 在這個圖的左下角和右上角體現(xiàn)了對刀具軌跡進行即時生成和對當前銑削的監(jiān) 測。在此圖的右下角，監(jiān)測切削扭矩、改變

30、進擊速率以及徑向和軸向的切削深度。 切削參數(shù)可以動態(tài)修改以保持合適的切削載荷。 a)b) 圖48.30 a-d對刀具軌跡即時生成案例 （a）.雙邊曲折路徑（b）.輪廓線路徑（c）.改變間距（d）.改變切削深度 圖48.31在AIMac下的自適應銃削 Face mill 080 mm Scanning-Hire mock End mill 0 10 nun Cofiljour-liiK rncde End mill 0 16 mm Scanniiiig-liine mode End mi JI 0 10 nun Scanning-Line cnodje 5 = 1000 rpm. F = 230

31、 mniinio RD = S mm. AD = 5 mm S = 2450 rpm. F = 346 rnnt/nniii RD= L6mm.AD = 3 mnn S= 1680 rpfiL F= 241 mm/niiiin. RD = 4.5 jtmil ,W = 2.1 nm 5 = 2450 rptOr F= 346 ram/mui RD = l-6min, .40 = 3.3 mm * o Oosed pocfcet 1 F2 Open pocket Closed dkn 4 End mill 0 10 mm ScanuLng-liDe nDodc End mill 0 6 mm S

32、canning-line mode End. mill6mm Scainnimg-lime mode Ball end mill 0 10 mm Sannin-Liine mode 5 = 2450 rpm. F = 346 ramvkii口 RD = 1.6 mm. AD = 3.8 juju S = 3553 rpm. F = 413 mnnniii RD= Umni.j4D = 2.l mm S = 3539 rpra_ F = 413 ram/nuim. RD= 12. miL AD = 2.1 nun 5 = 2580 iprOr F= 335 ffom/mLu RD = 13 mm

33、, .Ws 3.2 mm Closed slot 嚴1 5 Closed. sloL 卜0 G6 Open slot 7 Free Form F8 Center drill 03 nm Drilling fliMxte Drill 010 mm Drill mg mode Raw malerial, shape Finished shape S = 1154 rpm. F = 232 imnuini口 S =rpnL F = 1-80 mra/mi口 Blind hok lks Blind hole 自 “ 圖48.32在AIMac下的機械加工工藝 柔性加工系統(tǒng)和操作規(guī)劃系統(tǒng) 在機械加工中，柔

34、性加工系統(tǒng)和操作規(guī)劃系統(tǒng)已經(jīng)發(fā)展到可動態(tài)生成切削參 數(shù)。該系統(tǒng)可以根據(jù)總?cè)コ可缮a(chǎn)計劃。總?cè)コ渴歉鶕?jù)產(chǎn)品的初始形狀和 最終的完成形狀決定，他可分成加工基元和加工特性。該系統(tǒng)會根據(jù)檢測到的加 工特性生成切削參數(shù)。圖48.32顯示了加工順序和切削刀具的使用。切削參數(shù)確 定了試驗加工的形狀。數(shù)字仿形銑削系統(tǒng)可以生成刀具路徑或動態(tài) CL數(shù)據(jù)，根 據(jù)這些結果便可以獨立完成銑削加工而不需要任何數(shù)控程序。 48.5未來智能機床的關鍵技術 如同上一節(jié)，該節(jié)提出和研究了一些結構和技術。 然而，他們還沒有足夠的 成熟來被廣泛地應用在實踐中。所以，這些科研成果只能被限制在特定情況下使 用。 在圖48.33中概

35、述了實現(xiàn)未來智能機床的關鍵技術。 過程和加工質(zhì)量控制將 成為更重要的自適應控制。動態(tài)刀具軌跡的生成和制造過程中的切削參數(shù)修改被 要求實現(xiàn)靈活的加工操作和加工質(zhì)量控制。此外，智能過程控制是對加工過程質(zhì) 量控制進行切削程序和加工質(zhì)量的評估。必須用合理的方法來控制切削過程以及 通過合理的指標來評估加工質(zhì)量。因此考慮利用所獲取的學問、專業(yè)知識和關于 加工操作的技巧是非常必要的。 生產(chǎn)過程的規(guī)劃策略對于生成一個靈活和適應性的工作計劃是必需的。 一個 操作規(guī)劃策略也需要確定的切削刀具和參數(shù)。 為了生成自己的操作方案，產(chǎn)品數(shù) 據(jù)分析和加工特征識別顯得尤為重要。 Key lechnnlngie* (orKep

36、tual Cnnfinm Pructkrtl Motion control Adaptive ccnlrul A Process and qualiry control Mnniilfirino- ino 1VIUJI IllUl 11 JjLL t jC-113-1111. / Jnlc lligenl prcxrcss mon i tori ng Open ardinecture correpc Process planning - Opcnlion planning A Utilization of knowhow Learning of knowhowf A jTTcrwunsnmnrmroTmTijnmri Di strihuted com puli ng 圖48.33實現(xiàn)未來智能機床獲的關鍵技術 第一章可行性研究報告概述錯誤！未定義書簽 1.1項目名稱錯誤