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編號 無錫太湖學(xué)院 畢業(yè)設(shè)計（論文） 相關(guān)資料 題目： 定梁式數(shù)控雕刻機機械結(jié)構(gòu)設(shè)計 信機 系 機械工程及自動化專業(yè) 學(xué) 號： 　　　 0923164　　　　 學(xué)生姓名： 范　 俊 指導(dǎo)教師： 　 黃敏 （職稱：副教授） （職稱： ） 2013年5月25日 目 錄 一、畢業(yè)設(shè)計（論文）開題報告 二、畢業(yè)設(shè)計（論文）外文資料翻譯及原文 三、學(xué)生“畢業(yè)論文（論文）計劃、進度、檢查及落實表” 四、實習(xí)鑒定表 無錫太湖學(xué)院 畢業(yè)設(shè)計（論文） 開題報告 題目： 定梁式數(shù)控雕刻機機械結(jié)構(gòu)設(shè)計 信機 系 機械工程及自動化 專業(yè) 學(xué) 號： 0923164 學(xué)生姓名： 范 俊 指導(dǎo)教師： 黃敏 （職稱：副教授） （職稱： ） 2012年11月25日 課題來源 自擬。 科學(xué)依據(jù)（包括課題的科學(xué)意義；國內(nèi)外研究概況、水平和發(fā)展趨勢；應(yīng)用前景等） （1）課題科學(xué)意義 數(shù)控雕刻機是一種具備雕刻加工功能的數(shù)控機床。大都認(rèn)為雕刻機是使用小刀具、大功率和高速主軸電機的數(shù)控銑床。雕刻機的優(yōu)勢在雕刻，對零件表面的精細(xì)加工，是一種高效、高精度的數(shù)控機床。隨著模具工業(yè)和工藝美術(shù)品制造業(yè)的快速發(fā)展，國內(nèi)外市場對數(shù)控雕刻機的需求不斷擴大，特別是高端的數(shù)控雕銑中心，需求更為旺盛。在制鞋工業(yè)、運動器材工業(yè)、汽車輪胎制造業(yè)等工業(yè)領(lǐng)域有廣泛的應(yīng)用，特別是模具制造業(yè)必不可少的機床裝備。 （2）數(shù)控雕刻機的研究狀況及其發(fā)展前景 數(shù)控雕刻機以自身所具有的技術(shù)優(yōu)勢，加上合理的價格，已成為我國消費類電子零配件制造、小型精密模具制造、PCB電路板、五金制品、家具制造等行業(yè)重要的機床工具。另外，在LED鋁基板、工藝禮品、金屬電極、金屬眼鏡框加工等領(lǐng)域，也開始使用數(shù)控雕刻機。 隨著數(shù)控雕刻機應(yīng)用領(lǐng)域的不斷拓展，其市場規(guī)模也不斷擴大。據(jù)羅百輝調(diào)查，2002～2006年，數(shù)控雕刻機小批量應(yīng)用于模具加工、家具制造行業(yè)，處于市場導(dǎo)入期。隨著數(shù)控雕刻機技術(shù)的不斷成熟和價格趨于合理，其性價比逐漸得到業(yè)界的認(rèn)可，市場快速擴大。進入2007年我國數(shù)控雕刻機產(chǎn)銷量突破10000臺，產(chǎn)值超過15億元，標(biāo)志著國內(nèi)數(shù)控雕刻機產(chǎn)業(yè)進入高速成長期；從2007～2010年，在模具加工、家具與五金制造等行業(yè)需求繼續(xù)快速增長的同時，由智能手機、平板電腦、電子書、GPS等帶動的消費類電子零配件制造業(yè)的需求異軍突起，推動數(shù)控雕刻機行業(yè)迅速發(fā)展，2010年國內(nèi)數(shù)控雕刻機產(chǎn)量已突破4.5萬臺。 隨著下游各應(yīng)用領(lǐng)域?qū)Ξa(chǎn)品加工過程中的高精密、高效率、低耗能、低耗材的要求不斷提升，數(shù)控雕刻機自身技術(shù)不斷成熟，下游新興應(yīng)用領(lǐng)域不斷涌現(xiàn)，國內(nèi)人工成本的不斷增長，原有老舊設(shè)備的更新?lián)Q代等等，都將對數(shù)控雕刻機市場起到積極的推動作用。未來數(shù)控雕刻機行業(yè)將持續(xù)高速增長。結(jié)合各下游行業(yè)十二五規(guī)劃制定的發(fā)展目標(biāo)，羅百輝預(yù)計到2015年全國數(shù)控雕刻機產(chǎn)銷量將達(dá)到12萬臺。 在市場結(jié)構(gòu)方面，消費類電子產(chǎn)品零配件制造、模具制造、五金制品及家具制造等四大行業(yè)仍將是數(shù)控雕刻機的主要應(yīng)用領(lǐng)域。其中，隨著觸摸屏手機、平板電腦的滲透率不斷提高，未來消費類電子產(chǎn)品零配件制造行業(yè)對數(shù)控雕刻機需求將持續(xù)快速增長，到2015年，僅消費類電子產(chǎn)品零配件制造行業(yè)，對數(shù)控雕刻機需求量就將達(dá)到38000臺。 研究內(nèi)容 ① 了解數(shù)控雕刻機的工作原理，國內(nèi)外的研究發(fā)展現(xiàn)狀； ② 完成數(shù)控雕刻機機械總體方案設(shè)計； ③ 完成零部件的選型計算、結(jié)構(gòu)強度校核； ④ 熟練掌握有關(guān)計算機繪圖軟件，并繪制裝配圖和零件圖紙，折合A0不少于3張； ⑤ 完成設(shè)計說明書的撰寫，并翻譯外文資料1篇。 擬采取的研究方法、技術(shù)路線、實驗方案及可行性分析 到數(shù)控雕刻機加工工廠參觀，增強對雕刻機系統(tǒng)和結(jié)構(gòu)的認(rèn)識，構(gòu)思機床外部結(jié)構(gòu)。去學(xué)校圖書館或上網(wǎng)查找有關(guān)數(shù)控雕刻機改造的書籍，再對其系統(tǒng)內(nèi)部零件進行設(shè)計：機床主傳動系統(tǒng)的設(shè)計，機床進給系統(tǒng)的設(shè)計，機床主要零部件的設(shè)計計算。查閱有關(guān)雕刻機的資料，對其主要零件進行校核。撰寫設(shè)計書名書，完成雕刻機下體機裝配圖及各主要零件圖的繪制。 研究計劃及預(yù)期成果 研究計劃： 2012年11月17日-2013年1月13日：按照任務(wù)書要求查閱論文相關(guān)參考資料，填寫 畢業(yè)設(shè)計開題報告書，學(xué)習(xí)并翻譯一篇與畢業(yè) 設(shè)計相關(guān)的英文材料。 2013年1月15日-2013年3月5日：擬好論文框架，寫好第一章緒論，并構(gòu)思所需要 的圖紙。 2013年3月8日-2013年3月12日：按照要求修改畢業(yè)設(shè)計開題報告。 2013年3月14日-2013年4月11日：完成雕刻機機械結(jié)構(gòu)設(shè)計，完成機床主傳 動系統(tǒng)、進給系統(tǒng)的設(shè)計選擇及機床主要零部件 的設(shè)計計算，完成所需圖紙。 2013年4月12日-2013年4月25日：完成有關(guān)零部件的選型及校核計算，并校驗圖紙。 2013年4月26日-2013年5月20日：畢業(yè)論文撰寫和修改工作。 預(yù)期成果： 數(shù)控雕刻機機械結(jié)構(gòu)總體裝配圖及主要零部件圖，完成設(shè)計說明書的撰寫。 特色或創(chuàng)新之處 ① 機床底座采用鑄造結(jié)構(gòu)，確保了整體的穩(wěn)定性。 ② 機床的三軸運動形式采用刀具Y/Z軸進給運動，工作臺作X軸進給運動的定梁式結(jié)構(gòu)，增強了加工的穩(wěn)定性，保證了加工精度。 ③ 機床橫梁導(dǎo)軌的布局采用垂直向的空間式結(jié)構(gòu)，確保了加工的平穩(wěn)和精度。 已具備的條件和尚需解決的問題 ① 現(xiàn)已查閱到數(shù)控雕刻機改造的相關(guān)資料。 ② 需要查閱課本和相關(guān)資料，相互比較，以選取最佳方案。 指導(dǎo)教師意見 指導(dǎo)教師簽名： 年 月 日 教研室（學(xué)科組、研究所）意見 教研室主任簽名： 年 月 日 系意見 主管領(lǐng)導(dǎo)簽名： 年 月 日 英文原文 Research on a Novel Parallel Engraving Machine and its Key Technologies Abstract: In order to compensate the disadvantages of conventional engraving machine and exert the advantages of parallel mechanism, a novel parallel engraving machine is presented and some key technologies are studied in this paper. Mechanism performances are analyzed in terms of the first and the second order influence coefficient matrix firstly. So the sizes of mechanism, which are better for all the performance indices of both kinematics and dynamics, can be confirmed and the restriction due to considering only the first order influence coefficient matrix in the past is broken through. Therefore, the theory basis for designing the mechanism size of novel engraving machine with better performances is provided. In addition, method for tool path planning and control technology for engraving force is also studied in the paper. The proposed algorithm for tool path planning on curved surface can be applied to arbitrary spacial curved surface in theory, control technology for engraving force based on fuzzy neural network (FNN) has well adaptability to the changing environment. Research on teleoperation for parallel engraving machine based on B / S architecture resolves the key problems such as control mode, sharing mechanism for multiuser, real-time control for engraving job and real-time transmission for video information. Simulation results further show the feasibility and validity of the proposed methods. Keywords: parallel mechanism, engraving machine, influence coefficient, performance indices, tool path planning, force control, fuzzy neural network, teleoperation 1 Introduction Conventional computer engraving machine has played an important role in industries such as machinery machining, printing and dyeing and entertainment, but it has the inherent disadvantages such as cutting tool can be fed only along the fixed guideway, lower degree-of-freedom (DOF) of cutting tool, lower flexibility and mobility for machining etc. Parallel mechanism has the merits such as high mechanical stiffness, high load capacity, high precision, good dynamic performance etc (Zhen, H.; Ling-fu, K. & Yue-fa, F., 1997). According to the characteristics of parallel mechanism, it has been a hot research topic to apply parallel mechanism to the domain of future machining. By applying parallel mechanism to engraving domain, its inherent advantages can be fully exerted and the disadvantages of conventional engraving machine can be overcome or compensated. But as the special structure of parallel mechanism, the related theory and technology during its engraving is very different from that of conventional engraving machine, and it is a undeveloped research topic by now. In addition, with the development of computer network technology, the new concept and method such as network machining and manufacturing has become hot research topic (GQ, Huang & K.L,, Mak., 2001; Taylor, K. & Dalton, B., 2000; Ying-xue, Y. & Yong, L., 1999). A novel parallel engraving machine with six-axis linkage is proposed in this paper, which uses the 6-PUS parallel mechanism with 6-DOF as the prototype, and some key technologies such as size design, tool path planning, engraving force control and teleoperation are studied on this basis. 2. Confirming of mechanism type and engraving machine's size 2.1 Selection of mechanism and coordinate system The selection of mechanism type is the first step for designing novel engraving machine, the following reasons make us select the 6-PUS parallel mechanism for designing our engraving machine. Comparing with traditional mechanism, 6-PUS parallel mechanism uses base platform, three uprights layout and high rigidity framework structure and has the merits such as high modularization, high accuracy and low cost. Itsmodel is shown in Fig.1. Fig. 1. The model of 6-PUS parallel mechanism As shown in Fig.1, 6-PUS parallel mechanism consists of base platform, dynamic platform and 6 branch chains with same structure, every branch joins with base platform through prismatic pairs (P), slider of prismatic pairs joins with up end of the fixed length link through universal joint (U), down end of the fixed length link joins with dynamic platform through sphere hinge (S), so it is called 6-PUS parallel mechanism. The coordinate system of 6-PUS parallel engraving mechanism is shown in Fig. 2. In Fig.2, the geometry centers of base platform and dynamic platform plane are supposed as OB and op respectively. In every branch, the centers of prismatic pairs, universal joint and sphere hinge are marked with Ai, Bi,, and Ci (i = 1,2, ..., 6) respectively. Coordinate system OB-XBYBZB is fixed on base platform, taking {B} as briefly. The origin of {B} lies on geometry center of base platform's up plane, axis ZB is vertical with base platform and directs to up, axis YB directs to angle bisector of the first and second branch lead screw center line, and axis XB can be determined with right-hand rule. Supposing the coordinate system set on dynamic platform is op-xpypzp, taking {P} as briefly, its origin lies on geometry center of dynamic platform, the initial state of dynamic platform system is consistent with that of base platform system completely. Supposing the coordinate of op is (0,0, Z) in {B}, this configuration without relative rotation to every axis is the initial configuration of this mechanism, and Z changing with mechanism's size. On the basis of coordinate system mentioned, we use influence coefficient theory and the actual parameters of this mechanism to calculate the first and the second order influence coefficient matrix of every branch under different configuration. Then, we can get the first and the second order integrated influence coefficient matrix H of the whole mechanism. 和 The significance and detailed solution process for influence coefficient matrix is omitted here, for more information please refer (Zhen, H.; Ling-fu, K. & Yue-fa, F., 1997). Fig. 2. Coordinate system of 6-PUS parallel engraving mechanism 2.2 Mechanism performance analysis based on influence coefficient matrix The performance of engraving machine will change with its size. To find out the better size for all the performance indices of both kinematics and dynamics, we obtain a group of mechanisms by changing its parameters. These mechanisms' length of fixed length links (L) range between 45cm and 55cm (step is 1cm), radius of dynamic platform (R) range between 10cm and 20cm (Step is 1cm). Other parameters of the mechanism is unchanging, so we get 121 mechanisms totally. Taking these mechanisms as research object, we confirm the sample point for every mechanism in its workspace with algorithm PerformanceAnalysis, then calculate the first and the second order influence coefficient matrix in every point. Furthermore, calculate all the performance indices in every sample point and draw all the global performance atlas of 121 mechanisms ultimately. To describe conveniently, we abbreviate the first and the second order integrated influence coefficient matrix Hq to G and H, and use Gω, Hω and Gυ, Hυ as the angular velocity submatrix and linear velocity submatrix of the first and the second order integrated influence coefficient matrix respectively, namely, We can change mechanism's parameters and adjust variable's step in the algorithm PerformanceAnalysis to meet actual analysis. The algorithm is programmed with MATLAB and the global performance atlas of 6-PUS mechanism are drawn (see Fig. 3 to Fig. 8), then the mechanism's performance is analyzed using the atlas. Table 1 shows the results of sample point number (abbr. to SPN) for 121 mechanisms respectively, the fixed link length of mechanism with sequence number (abbr. to SN) 1 is 45cm, its radius of dynamic platform is 10cm, the fixed link length of mechanism with SN 121 is 55cm, its radium of dynamic platform is 20cm, the rest may be deduced by analogy. In addition, table 2 gives the performance indices of some mechanism only, where the mean of SN is same as in table 1. Description for algorithm PerformanceAnalysis: PerformanceAnalysis Begin For L = 45 To 55 / / scope of fixed length link For R = 10 To 20 / / scope of radius of dynamic platform SamplePointNumber = 0; / / initialization sample point number is zero for every mechanism For x =-Maximum To + Maximum moving along Axis X Step 4cm For y =-Maximum To + Maximum moving along Axis Y Step 4cm For z =-Maximum To + Maximum moving along Axis Z Step 4cm For α =-Maximum To + Maximum rotating around Axis X Step 12 ° For β =-Maximum To + Maximum rotating around Axis Y Step 12 ° For γ =-Maximum To + Maximum rotating around Axis Z Step 12 ° If sample point (x, y, z, α, β, γ)? Reachable point of mechanism's workspace Calculating the first order influence coefficient matrix and its Frobenius norm at current point; If The first order influence coefficient matrix is ??not singular SamplePointNumber = SamplePointNumber +1; Calculating the second order influence coefficient matrix and its Frobenius norm calculating condition number at this point with formula and accumulating sum of performance indices; / / detailed formula is given in the following of this section Endif Endif Endfor Endfor Endfor Endfor Endfor Endfor Calculating all the performance indices of the mechanism at current size and append the results to corresponding data files for different performance index; / / performance index of the mechanism =(accumulating sum of performance indices at all sample points) / SamplePointNumber / / There are six data files for performance indices totally: angular velocity, linear velocity,angular acceleration, linear acceleration, force and moment, inertia force Endfor Endfor Drawing all the global performance atlas of 6-PUS mechanism by all the index data files (Every data file includes the information of 121 mechanisms); / / There are six performances atlas totally: angular velocity, linear velocity, angular acceleration, linear acceleration, force and moment, inertia force End Table 1. The SPN of 121 mechanisms in experiment SN SPN 六個性能指標(biāo) 角速度 線速度 角加速度 線加速度 力和力矩 慣性力 1 30962 0.17276 0.17442 0.06236 0.11315 0.01521 0.37454 2 28074 0.18248 0.18171 0.08075 0.13276 0.01456 0.40421 3 25848 0.19128 0.18836 0.09932 0.15184 0.01396 0.43136 4 23252 0.20087 0.19545 0.11897 0.17225 0.01348 0.46030 ... ... ... ... ... ... ... ... 59 42390 0.21105 0.18995 0.10050 0.01304 0.01304 0.40233 60 37410 0.21915 0.19537 0.11308 0.17355 0.01257 0.42606 61 32446 0.22717 0.20041 0.12312 0.19230 0.01216 0.44929 ... ... ... ... ... ... ... ... 119 28942 0.25779 0.20680 0.12265 0.22596 0.01064 0.47030 120 23998 0.26786 0.21185 0.12116 0.24139 0.01041 0.49500 121 19828 0.27714 0.21610 0.11399 0.25527 0.01017 0.51745 Table 2. Six performance indices of some mechanisms 2.2.1 Analysis of kinematics performance indices 2.2.1.1 Global performance indices of angular velocity and linear velocity As the influence coefficient G of engraving mechanism is not a constant matrix, it makes the measuring index for parallel mechanism based on G not to be a constant matrix also, so we can't utilize one value to measure the good or bad of the dexterity, isotropy and controlling accuracy (Xi-juan, G., 2002). Here, we define parallel mechanism global performance indices of angular velocity and linear velocity as following respectively Where W is the reachable workspace of mechanism, anddenote the condition numbers for angular velocity and linear velocity respectively (Where | | · | | denotes Frobenius norm of matrix, superscript '+' denotes generalized inverse matrix, the same mean as following). We can get the performance indices' value of the angular velocity and linear velocity according to the condition numbers of every mechanism's sample points. Replacing the underlined part in algorithm PerformanceAnalysis with two formulas in (1) respectively, we can draw the performance atlas for angular velocity and linear velocity as shown in Fig.3 and fig.4 based on 121 mechanisms' indices values ??of angular velocity and linear velocity. According to the rule that the bigger ηJ (J ∈ {Gω, Gv}), the higher dexterity and controlling accuracy of the mechanism, from Fig.3 we can see that the mechanism performance index of angular velocity is not changing with the link length when the changing range of R is not big, but it has the trend that the bigger R, the better Fig. 3. Atlas of angular velocity global performance Fig. 4. Atlas of linear velocity global performance performance index of angular velocity, furthermore, the index of mechanism angular velocity is better when L = 46.5cm ~ 49.5cm and R = 19.5cm, namely, the output error of angular velocity is smaller. Similarly, from Fig.4 we know that the mechanism index of linear velocity is better when L = 45cm ~ 48cm and R = 19cm, that is to say,the output error of linear velocity is smaller. 2.2.1.2 Global performance indices of angular acceleration and linear acceleration.Considering the influences on acceleration of both the first and the second order influence coefficient matrix, the condition numbers of angular acceleration and linear acceleration for 6-DOF parallel mechanism are (Xi-juan, G., 2002; Xi-juan, G. & Zhen, H., 2002) Where, a and b is error coefficient.So the global performance indices of angularacceleration and linear acceleration for parallelengraving mechanism can be defined as Where Supposed the mechanism error is smaller than 2% (that is, a = b = 0.02), replacing the underlined part in algorithm .PerformanceAnalysis with formula (4), we can draw the performance atlas for angular acceleration and linear acceleration as shown in Fig.5 and Fig.6. As same as the evaluating method for velocity performance index, from Fig. 5 we can see that the angle acceleration performance of mechanism is better when nearly L = 45cm ~ 47cm and R = 16cm ~ 20cm, output error is smaller accordingly. Among the 121 mechanism we studied, its maximum is 0.16399. Fig.5. Atlas of angular acceleration global performance By observing Fig.6 carefully, we know that performance of linear acceleration is better when nearly L=45cm~48cm and R=19.5cm, accordingly, output error should be smaller. From above analysis, we know that mechanism size with good indices for linear velocity and linear acceleration is coincidence in some degree among the 121 mechanisms we studied, but performance index of angular velocity and angular acceleration may not the best in the same size, so it can’t get coincidence. Thus, our analysis will be helpful for designing and choosing mechanism by actual needs. Similarly, analyzing method of kinematics performance indices is the same when other parameters of the mechanism are changed. Fig. 6 . Atlas of linear acceleration global performance 2.2.2 Analysis of dynamics performance indices 2.2.2.1 Analysis of power and moment performance Index. The condition number of power and moment performance index based on the first order influence coefficient matrix of power GF for 6-DOF parallel mechanism can be defined as(Xi-juan,G.,2002) Similarly, we define global performance index of power and moment for 6-DOF parallel mechanism as We suppose that power and moment of parallel mechanism is isotropy when ηJ=1. With formula (5) as condition number, replacing the underlined part in algorithm with formula (6), we can draw the performance atlas for power and moment as shown in Fig.7. From Fig. 7 we can see in the size range of our experiment the performance index for power and moment would have little change with the link length when the radius of dynamic platform is less then 14cm. The performanc index for mechanism’s power and moment will be bigger when L=45cm~46cm and radius of dynamic platform R=10cm,here, performance of power and moment will be better. Fig. 7. Atlas of global performance of force and moment 2.2.2.2 Analysis of inertia force performance index Considering both the first and the second order influence coefficient matrix, the condition number of inertia force for 6-DOF parallel mechanism is defined as(Xi-juan,G.,2002) Where [Gω