機(jī)床立柱加工工藝及專用刀具設(shè)計(jì)

機(jī)床立柱加工工藝及專用刀具設(shè)計(jì),機(jī)床,立柱,加工,工藝,專用,刀具,設(shè)計(jì) 畢業(yè)設(shè)計(jì)中英文翻譯 學(xué)生姓名： 學(xué)號(hào)： 學(xué) 院： 機(jī)械設(shè)計(jì)制造及其自動(dòng)化 專 業(yè)： 指導(dǎo)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 machining commands in the NC programs, they are not generally allowed to be changed during machining operations. Therefore NC programs must be adequately prepared and verified in advance, which requires extensive amounts of time and effort. Moreover, NC programs with fixed commands are not responsive to unpredictable changes, such as job delay, job insertion, and machine breakdown found on machining shop floors. Shirase proposed a new architecture to control the cutting process autonomously without NC programs. Figure 48.29 shows the conceptual structure of autonomous and intelligent machine tools (AIMac). AIMac consists of four functional modules called management, strategy, prediction, and observation. All functional modules are connected with each other to share cutting information. Fig. 48.29 Conceptual structure of AIMac Digital Copy Milling for Real-Time Tool-Path Generation A technique called digital copy milling has been developed to control a CNC machine tool directly. The digital copy milling system can generate tool paths in real time based on the principle of traditional copy milling. In digital copy milling, a tracing probe and a master model 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 generated dynamically according to the motion of the virtual tracing probe in real time. In the digital copy milling, cutter locations are generated autonomously, and an NC machine tool can be instructed to perform milling operation without NC programs. Additionally, not only stepover, but also radial and axial depths of cut can be modified, as shown in Fig. 48.30. Also, digital copy milling can generate new tool paths to avoid cutting problems and change the machining sequence during operation [48.12]. Furthermore, the capability for in-process cutting parameters modification was demonstrated, as shown in Fig. 48.31 [48.13]. Real-time tool-path generation and the monitored actual milling 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 shown in the lowerright corner of this figure. The cutting parameters can be modified dynamically to maintain the cutting load. Fig. 48.30a–d Example of real-time tool-path generation. (a) Bilateral zigzag paths; (b) contouring paths; (c) change of stepover; (d) change of cutting depth Fig. 48.31 Adaptive milling on AIMac Fig. 48.32 Results of machining process planning on AIMac Flexible Process and Operation Planning System A flexible process and operation planning system has been developed to generate cutting parameters dynamically for machining operation. The system can generate the production plan from the total removal volume (TRV). The TRV is extracted from the initial and finished shapes of the product and is divided into machining primitives or machining features. The flexible process and operation planning system can generate cutting parameters according to the machining features detected. Figure 48.32 shows the operation sequence and cutting tools to be used. Cutting parameters are determined for the experimental machining shape. The digital copy milling system can generate the tool paths or CL data dynamically according to these results and perform the autonomous milling operation without requiring any NC program. 48.5 Key Technologies for Future Intelligent Machine Tool Several architectures and technologies have been proposed and investigated as mentioned in the previous sections. However, they are not yet mature enough to be widely applied in practice, and the achievements of these technologies are limited to specific cases. Achievements of key technologies for future intelligent machine tools are summarized in Fig. 48.33. Process and machining quality control will become more important than adaptive control. Dynamic toolpath generation and in-process cutting parameters modification are required to realize flexible machining operation for process and machining quality control. Additionally, intelligent process monitoring is needed to evaluate the cutting process and machining quality for process and machining quality control. A reasonable strategy to control the cutting process and a reasonable index to evaluate machining quality are required. It is therefore necessary to consider utilization and learning of knowledge, knowhow, and skill regarding machining Operations. A process planning strategy with which one can generate flexible and adaptive working plans is required. An operation planning strategy is also required to determine the cutting tool and parameters. Product data analysis and machining feature recognition are important issues in order to generate operation plans autonomously. Sections 48.4.2–48.5 are quoted from [48.14]. Fig. 48.33 Achievements of key technologies for future intelligent machine tools 譯文： 48.4.4 智能機(jī)床 整個(gè)傳統(tǒng)數(shù)控機(jī)床的機(jī)械加工是在預(yù)定的數(shù)控程序下進(jìn)行的。一旦切削條件（如切削深度和進(jìn)給量）在數(shù)控程序指令中被指定，在機(jī)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(shí)間和精力用來提前準(zhǔn)備和驗(yàn)證。此外，基于固定命令的數(shù)控程序在遇到不可預(yù)知的變化時(shí)不會(huì)響應(yīng)，比如工作延遲和加工車間中的機(jī)器故障。 Shirase提出了一種新的結(jié)構(gòu)在沒有數(shù)控程序的情況下可以自動(dòng)控制切削過程。圖48.29顯示了智能機(jī)床概念結(jié)構(gòu)。AIMAC包括四個(gè)功能模塊稱為管理、策略、預(yù)測(cè)和觀察。所有功能模塊都與彼此分享切削信息。 圖48.29 AIMac的概念結(jié)構(gòu) l 數(shù)字仿形銑削---對(duì)刀具軌跡進(jìn)行實(shí)時(shí)生成 數(shù)字仿形銑削技術(shù)被研發(fā)出來后，它可以直接控制數(shù)控機(jī)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(shí)生成刀具路徑。在數(shù)字仿形銑削中，傳統(tǒng)仿形銑削中的跟蹤探測(cè)器和主模型通過計(jì)算機(jī)用三維虛擬模型表現(xiàn)出來。虛擬跟蹤探測(cè)器模擬虛擬主模型，根據(jù)動(dòng)態(tài)的虛擬軌跡實(shí)時(shí)生成刀具坐標(biāo)。在數(shù)字仿形銑削中，刀具坐標(biāo)可自主生成，數(shù)控機(jī)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(shí)，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(duì)于切割過程中的參數(shù)修改能力也得到了證實(shí)，如圖48.31[48.13]。在這個(gè)圖的左下角和右上角體現(xiàn)了對(duì)刀具軌跡進(jìn)行即時(shí)生成和對(duì)當(dāng)前銑削的監(jiān)測(cè)。在此圖的右下角，監(jiān)測(cè)切削扭矩、改變進(jìn)擊速率以及徑向和軸向的切削深度。切削參數(shù)可以動(dòng)態(tài)修改以保持合適的切削載荷。 圖48.30 a-d對(duì)刀具軌跡即時(shí)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(yīng)銑削 圖48.32 在AIMac下的機(jī)械加工工藝 l 柔性加工系統(tǒng)和操作規(guī)劃系統(tǒng) 在機(jī)械加工中，柔性加工系統(tǒng)和操作規(guī)劃系統(tǒng)已經(jīng)發(fā)展到可動(dòng)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(jì)劃?？?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(huì)根據(jù)檢測(cè)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(yàn)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(dòng)態(tài)CL數(shù)據(jù)，根據(jù)這些結(jié)果便可以獨(dú)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(jī)床的關(guān)鍵技術(shù) 如同上一節(jié)，該節(jié)提出和研究了一些結(jié)構(gòu)和技術(shù)。然而，他們還沒有足夠的成熟來被廣泛地應(yīng)用在實(shí)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中概述了實(shí)現(xiàn)未來智能機(jī)床的關(guān)鍵技術(shù)。過程和加工質(zhì)量控制將成為更重要的自適應(yīng)控制。動(dòng)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(shí)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(duì)加工過程質(zhì)量控制進(jìn)行切削程序和加工質(zhì)量的評(píng)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(biāo)來評(píng)估加工質(zhì)量。因此考慮利用所獲取的學(xué)問、專業(yè)知識(shí)和關(guān)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(duì)于生成一個(gè)靈活和適應(yīng)性的工作計(jì)劃是必需的。一個(gè)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(shí)別顯得尤為重要。 圖48.33實(shí)現(xiàn)未來智能機(jī)床獲的關(guān)鍵技術(shù)