锻造操作机上架回旋机构设计

第一章 引言1.1 本课题的意义锻造操作机是锻造车间实现锻造自动化的关键设备，用于夹持锻件配合压机完成锻造工艺动作。在大锻件生产中，锻造操作机更是必不可少的设备。锻造操作机在20世纪60年代初就已问世，近二、三十年更是得到了迅速的发展。最早是在美国、前苏联，而后在德国、英国、日本等国发展起来，并成为系列化产品进入工业生产。最初的操作机多为全机械传动，随着科学技术的发展，到60、70年代出现了混合传动和全液压传动、结构紧凑、操作灵活的锻造操作机。它与压机配合使用，提高了生产效率及最大锻件质量。80年代以后，随着大型装备制造的快速发展，对大锻件生产又提出了更高的要求，促进了锻造操作机技术的发展，主要表现在对锻造操作机的需求量不断增加，对锻造操作机的最大锻件质量要求大大提高，引起了各国对锻造操作机在锻造生产作用的重视。我国锻造操作机起步于70年代，开始只能由一些锻造厂自己制造有轨锻造操作机，这些操作机结构简单，钳子的张合夹紧靠与吊钳分离开的电动方头扳手来完成，因而夹紧锻件不方便，只能用于钢锭开坯、拨料。随着国民经济的发展，80年代开始研制出全机械传动和少数液压传动有轨操作机。随后，小型液压传动有轨操作机得到发展，并出现了液压传动无轨操作机。90年代初期我国自行设计制造的100kN锻造操作机主要技术性能已达到世界80年代水平，该台锻造操作机于1992年5月在太原试制成功。近年来，核电、造船、化工、国防等领域的大型锻件精确高效制造迫切需要重载锻造操作机。重载锻造操作机发展水平的落后制约了我国的大装备制造能力，部分大型装备的关键构件完全依赖进口。重载锻造操作机直接影响国家重大工程的实施和国民经济的发展，开展重载锻造操作机的研究具有重要战略意义。1.2 锻造操作机的国内外发展现状大型锻造操作机属于当前世界最大的多自由度重载机器人，属于机、电、液高度一体化的复杂装备，它是万吨锻造压机的重要配套设备，也是国家经济建设急需的重大机械装备之一。并且，大型锻件制造业是装备制造业的基础行业，是关系到国家安全和国家经济命脉的战略性行业，其发展水平是衡量国家综合国力的重要标志。通过深入开展大型锻造操作机的研究工作，将逐步实现大型锻造操作机的国产化，对提升我国大型装备及关键零部件的自主设计和制造能力、满足国家经济建设的需求结束我国不能设计大型锻造操作机的历史都具有重要的社会意义和经济效益。一、大型锻造操作机的发展历史锻造操作机最早出现在美国和原苏联，而后在日本、英国、奥地利等国发展起来，并成为系列化产品进入工业性生产。最初的操作机多为全机械传动，60、70年代出现了混合传动和全液压传动、结构紧凑、操作灵活的锻造操作机。到了80年代，各国对锻造操作机的设计、制造、技术改造方面又有了更高的要求，不断改进结构及生产工艺，促进了锻压技术的发展。特别是锻造操作机的需求量不断增加，引起了国内外大、中型企业对锻造操作机在生产中作用的重视。90年代中期，国外大型锻造操作机技术已经成熟，大型操作机与30000kN自由锻造水压机联动操作，不断提高了水压机生产能力。我国锻造操作机起步于60年代，开始只能由某些工厂自己制造有轨操作机。90年代初期，我国自行设计制造的100kN锻造操作机于1992年5月在太原试制成功，其主要技术性能已达到世界80年代水平，能替代同类进口产品。至今，我国自主研发投产的全液压锻造操作机最大夹持能力也只有500kN。世界上装备的万吨级自由锻造压机近30台，最大的模锻水压机载荷能力高达7.5万吨，最大的六自由度锻造操作机操作力矩达7500kNm，最大承载能力高达2500kN。目前，我国已具备了万吨级锻压装备的设计与制造能力，如中国一重自主设计、自主制造的世界上最先进的150MN自由锻造水压机，2006年末已经投产使用，但与之配套的大型锻造操作机仍在研发当中。二、大型锻造操作机的研究现状国内外大型锻造操作机的研究现状锻造操作机作为进行锻造工艺的重要设备，众多国外公司对其进行了系统化研究，目前，德国DDS公司、韩国HBE PRESS公司以及捷克ZDAS公司的锻造操作机的制造水平处在世界前列。其中，德国DDS公司和WEPUKO公司是世界著名的锻造操作机专业研发、制造企业，在重型锻造操作机研制领域具有70多年的历史。此外，日本三菱长琦生产的操作机因拥有高速、高精度的机械手及控制系统而著称。国内锻造操作机的研究起步较晚，在一些技术方面与国外相比还有一定的差距。与万吨压机配套的大型锻造操作机全部采用进口设备，自主开发的大型锻造操作机至今尚未问世，如中国一重与上海交大联合开发的1600kN锻造操作机和北方重工自主开发的2000kN锻造操作机的整机水平还有待于进一步验证。我国与大型锻造操作机相关的研究项目为解决我国重大装备制造中一批关键技术和共性技术问题，实现重大装备及其成套技术的自主研发，科技部在“十一五”国家科技支撑计划中设立了“大型铸锻件制造关键技术及装备研制”项目，在重点完成的工作中明确提出“150MN自由锻造水压机及配套设备关键技术研究”和“165MN自由锻造油压机及配套设备关键技术研究”。第一个课题主要开展大型自由锻造水压机整机设计、模态分析、预应力框架结构整体振动及疲劳分析，开展快换机构设计和控制系统设计研究，研制配套操作机；第二个课题自主开展大型自由锻造油压机整机设计、快换机构设计、控制系统设计技术研究和关键部件研制，攻克多功能操作机设计技术、驱动和控制系统设计技术研究和关键结构件制造技术等，掌握核心技术，开展压机与操作机及辅助装备联动协调控制技术研究等。上述两个课题，对掌握大型操作机核心技术、攻破我国重大技术装备的生产瓶颈、提高特大型自由锻件的制造技术水平与制造能力起着关键性的作用。2006年，上海交通大学、浙江大学、中南大学清华大学、大连理工大学、华中科技大学共同承担了国家科技部“973”计划中“巨型重载操作装备的基础科学问题”项目，围绕“多自由度重载操作机构构型与操作性能的映射规律”“重载操作装备的界面行为与失效机理”“重载操作装备的多源能量传递规律与动态控制”三个基础科学问题，开展了7个课题研究，包括大型构件制造操作运动轨迹建模、重载装备多自由度操作性能度量与机构设计原理、低速非连续工况下重载装备界面行为与力学特征、大尺度重型构件稳定夹持原理与夹持系统驱动策略、大流量电液伺服系统的介质流动规律、重载大惯量装备的快速协调控制和巨型重载操作装备的性能仿真与优化等。从基础研究的角度，揭示了巨型重载操作装备的操作灵活性、力承载能力、刚度等性能与机构构型的映射规律。此课题为我国巨型重载操作装备的研究提供了理论基础，同时，也为配套操作机的研究提供了进一步的可行性。三、大型锻造操作机的技术特征大型锻造操作机和万吨锻造压机是配合在一起联合工作的，工作过程中操作机保持着频繁的重复动作，对其性能的要求为动作速度高、空行程时间短、精整时定位准确，以达到快速锻造，并得到尺寸精确的锻件。与加工装备相比，大型操作机的特点是载荷大、惯量大、自由度多、操控能力强。大型锻造操作机的主要技术特征:一是在重载操作条件下，操作机构件的分布式柔性变形直接影响末端执行器的操作精度。因此，在装备的机构设计中，既要保证操作装备在整个工作空间中具有理想的刚度特性，又要通过运动学设计对结构变形在装备运动链中的传递特性进行控制。此外，锻造操作机长期在非连续工作条件下进行操作，其动力学性能在空载和负载操作情况下存在显著差别。二是大型锻造操作机制造成本高，设计与制造周期长，通常采用单台制造模式。重载操作机通常很难通过物理样机实验对其操作性能进行分析和验证，因此，计算机数值模拟是锻造操作机设计、性能评估与优化的重要支撑技术。第二章 锻造操作机简介锻造操作机（manipulator for forging ）用于夹持钢锭或坯料进行锻造操作及辅助操作的机械设备。 所谓，“10吨操作机”，是指该操作机可夹持的钢锭最大重量为十吨。2.1 基本含义用以夹持锻坯配合水压机或锻锤完成送进、转动、调头等主要动作的辅助锻压机械。锻造操作机有助于改善劳动条件，提高生产效率。根据需要，操作机也可用于装炉、出炉，并可实现遥控和与主机联动。操作机结构分有轨和无轨两种，其传动方式有机械式、液压式和混合式等。此外，还有专门用于某些辅助工序的操作机，如装取料操作机和工具操作机等。为了配合操作机的工作，有时 图2-1 锻造操作机还配置锻坯回转台，以方便锻坯的调头。在模锻和大件冲压中，机械手的应用已日益普遍，这样的机械手实际上是一种自动的锻造操作机。 主要用于750kg空气锤、1000-2000kg电液锤、模锻锤或其它相应吨位的锻锤，是我国锻造行业最先进的设备之一。 2.2 操作设备采用全液压传动，高集成阀块，超大流量通径，使系统压力损失少 密封性能高，油温控制好。 匠心独特的油路设计，真正使液压系统处在最佳状态，即使在长期大负荷情况下工作，也能轻松胜任。 运动系统采用了摆线齿轮马达和渐开线减速机组合，完美地实现了大车的无级变速行走、台架回转。 三级连动机构使钳口平行升降，钳杆倾斜，360度旋转，三维空间任意灵活转动。 图2-2锻造操作机机械手造型美观，结构紧凑，转动极其灵活，能出色地完成庞大的操作机无法完成的动作，让操作工体验到人机合一、随心所欲的感觉，充分体现操作机向机械手转变的根本意义。 锻造操作机适用于锻造和锻压行业，与各种自由锻锤及压机配合，能完成坯料成型的各种工序；对减轻劳动强度、提高生产效率60%以上；是锻造锻压行业不可缺少的辅助设备。 锻造操作机分类锻造操作机分为：直移式、回转式、平移式等多种运动形式，全机械、全液压、机械液压混合等多种驱动形式，可以从各方面满足不同用户的需要。 锻造操作机功能操作机具有以下动作功能：大车在轨道上自由行走；钳架前后升降、倾斜；钳头夹持、松开、旋转等。大车架采用整体框架式结构，由电机或马达驱动。钳架升降有钢丝绳或油缸带动，可实现前后同步升降或分别升降，使钳架到达水平或实现一定角度的倾斜。钳头夹紧由大螺距丝杆或油缸带动夹持拉杆水平移动实现，并且有缓冲保险装置。钳头旋转由电机减速机带动，并设有过载保护装置。钳架的前后、两侧及钳架与升降机之间均设有防振动的缓冲装置（另有大量配件供应）。 2.3 操作机的结构 10吨操作机是由四部分所组成，其结构示意如图2-3所示。 (1)升降机构：包括前提升油缸12、后提升油缸9、活塞7和13、活塞杆6和14、活动架19、沿块5以及弹簧24等。(2)夹紧机构：包括旋转滑阀26、夹紧油缸22活塞23、活塞杆21、钳壳17、夹紧滑块18、夹臂16和钳口15等。图2-3 10吨操作机结构示意图 (3)旋转机构：包括电动机l、制动器2、行星减速器3、减速器4与空心铀20等。 (4)大车行走机构：包括电动机27、减速器35、车轮28、车体29等。2.3.1 升降机构升降机构主要是为实现柸料的提升、下降、倾斜等动作，以满足锻造工艺过程的需要。升降机构由前提升机构、后提升机构、活动架等三部分所组成。2.3.2夹紧机构 夹紧机构主要用来夹持坯料、锻件或钢锭。 夹紧机构可以分成钳头和夹紧油缸俯两大部分，它们分别固定在空心轴的两抵钳头在前端，夹紧油缸在后端。 (1)钳头 钳头的结构如图2-4所示。两个钳口l通过销轴l0分别与夹臂3的一端铰接。小轴9穿过夹臂中间的孔，使夹臂小揣固定在钳壳2上，这样，夹臂便形成可以绕小轴回转的杠杆。夹臂的另一端通道销轴4与连板5铰接。连板又通过销轴8与夹紧滑块6相连。活塞杆7则以螺纹与夹紧滑块构成一体。图2-4 钳头 当活塞杆在夹紧油缸的拉力作用下，带动滑块和连板向后(即向左)移动时，上夹臂绕小轴作顺时钟方向转动，下夹臂臂绕小轴作逆晌针方向转动，使两钳口间的距离越来越小，坯料被夹紧。当活塞杆在夹紧油缸的推力作用下，推动滑块、连板向前(即向右)移动时，上夹臂绕小轴作逆时针方向转动，下夹臂绕小轴作顺时针方向转动，两钳口的距离越来越大，于是刨门钳口便张开。钳口与夹臀铰接是为了扩大夹持坯料的尺寸范围。如当夹持断面尺寸较大的钢锭或坯料时，两个钳口可以绕销铀向钳头内转动，而当夹持断面尺寸较小的钢锭或坯料时，两个钳口就绕销轴向钳头外转动，使钳口与被夹持的钢锭或坯料始终保持有足够的接触面积，被夹持的钢锭或坯料就不易松脱。 (2)夹紧油缸 夹紧油缸是操作机产生夹紧力的机构，在它的拉力或推力作用下，使钳头的钳口完成对钢锭、坯料或锻件的夹紧与张开动作。 夹紧油缸又可分成两大部分，一部分为油缸，另一部分为旋转滑阀。词条图册更多图册 2.3.3大车行走机构 大车行走机构承担着操作机自身的全部重量和操作机所夹持的钢锭、坯料或锻件的重量而在轨道上运行，完成锻造时需要坯料进退的动作。 大车行走机构由车体和行走机构两部分组成。 (1)车体 车体承担着操作机自身的重量和被夹持件的重量，它的结构如图13所示。车体的底座1支承在四个车轮9的铀承上。八个定位块l o用以保证车轮与车体的相关位置。托扳13焊接在底座尾部，托看行走机构的电动机3、减速器40在底座上固定着两根前立柱7和两根后立柱6，四根立柱又都与车顶11固定在一起。在两根前立柱间有前导板8，为活动架的前部升降导向部位。雨棍后立柱间则装有后导板12，后提升机构的升降滑块就在其问上、下滑动。车顶是装置液压系统的油箱、电动机、油泵、蓄能器、各种阀类等部件的地方，同时又支承着升降机构的油缸。图2-5 大车行走机构 第三章 旋转机构设计3.1 旋转机构的组成 please contact Q 3053703061 give you more perfect drawings附录II 外文文献原文A formal theory for estimating defeaturing -induced engineering analysis errorsSankara Hari Gopalakrishnan, Krishnan SureshDepartment of Mechanical Engineering, University of Wisconsin, Madison, WI 53706, United StatesReceived 13 January 2006; accepted 30 September 2006AbstractDefeaturing is a popular CAD/CAE simplification technique that suppresses small or irrelevant features within a CAD model to speed-up downstream processes such as finite element analysis. Unfortunately, defeaturing inevitably leads to analysis errors that are not easily quantifiable within the current theoretical framework.In this paper, we provide a rigorous theory for swiftly computing such defeaturing -induced engineering analysis errors. In particular, we focus on problems where the features being suppressed are cutouts of arbitrary shape and size within the body. The proposed theory exploits the adjoint formulation of boundary value problems to arrive at strict bounds on defeaturing induced analysis errors. The theory is illustrated through numerical examples.Keywords: Defeaturing; Engineering analysis; Error estimation; CAD/CAE1. IntroductionMechanical artifacts typically contain numerous geometric features. However, not all features are critical during engineering analysis. Irrelevant features are often suppressed or defeatured, prior to analysis, leading to increased automation and computational speed-up.For example, consider a brake rotor illustrated in Fig. 1(a). The rotor contains over 50 distinct features, but not all of these are relevant during, say, a thermal analysis. A defeatured brake rotor is illustrated in Fig. 1(b). While the finite element analysis of the full-featured model in Fig. 1(a) required over 150,000 degrees of freedom, the defeatured model in Fig. 1(b) required 25,000 DOF, leading to a significant computational speed-up.Fig. 1. (a) A brake rotor and (b) its defeatured version.Besides an improvement in speed, there is usually an increased level of automation in that it is easier to automate finite element mesh generation of a defeatured component 1,2. Memory requirements also decrease, while condition number of the discretized system improves;the latter plays an important role in iterative linear system solvers 3.Defeaturing, however, invariably results in an unknown perturbation of the underlying field. The perturbation may be small and localized or large and spread-out, depending on various factors. For example, in a thermal problem, suppose one deletes a feature; the perturbation is localized provided: (1) the net heat flux on the boundary of the feature is zero, and (2) no new heat sources are created when the feature is suppressed; see 4 for exceptions to these rules. Physical features that exhibit this property are called self-equilibrating 5. Similarly results exist for structural problems.From a defeaturing perspective, such self-equilibrating features are not of concern if the features are far from the region of interest. However, one must be cautious if the features are close to the regions of interest.On the other hand, non-self-equilibrating features are of even higher concern. Their suppression can theoretically be felt everywhere within the system, and can thus pose a major challenge during analysis.Currently, there are no systematic procedures for estimating the potential impact of defeaturing in either of the above two cases. One must rely on engineering judgment and experience.In this paper, we develop a theory to estimate the impact of defeaturing on engineering analysis in an automated fashion. In particular, we focus on problems where the features being suppressed are cutouts of arbitrary shape and size within the body. Two mathematical concepts, namely adjoint formulation and monotonicity analysis, are combined into a unifying theory to address both self-equilibrating and non-self-equilibrating features. Numerical examples involving 2nd order scalar partial differential equations are provided to substantiate the theory.The remainder of the paper is organized as follows. In Section 2, we summarize prior work on defeaturing. In Section 3, we address defeaturing induced analysis errors, and discuss the proposed methodology. Results from numerical experiments are provided in Section 4. A by-product of the proposed work on rapid design exploration is discussed in Section 5. Finally, conclusions and open issues are discussed in Section 6.2. Prior workThe defeaturing process can be categorized into three phases:Identification: what features should one suppress?Suppression: how does one suppress the feature in an automated and geometrically consistent manner?Analysis: what is the consequence of the suppression?The first phase has received extensive attention in the literature. For example, the size and relative location of a feature is often used as a metric in identification 2,6. In addition, physically meaningful mechanical criterion/heuristics have also been proposed for identifying such features 1,7.To automate the geometric process of defeaturing, the authors in 8 develop a set of geometric rules, while the authors in 9 use face clustering strategy and the authors in 10 use plane splitting techniques. Indeed, automated geometric defeaturing has matured to a point where commercial defeaturing /healing packages are now available 11,12. But note that these commercial packages provide a purely geometric solution to the problem. they must be used with care since there are no guarantees on the ensuing analysis errors. In addition, open geometric issues remain and are being addressed 13.The focus of this paper is on the third phase, namely, post defeaturing analysis, i.e., to develop a systematic methodology through which defeaturing -induced errors can be computed. We should mention here the related work on reanalysis. The objective of reanalysis is to swiftly compute the response of a modified system by using previous simulations. One of the key developments in reanalysis is the famous ShermanMorrison and Woodbury formula 14 that allows the swift computation of the inverse of a perturbed stiffness matrix; other variations of this based on Krylov subspace techniques have been proposed 1517. Such reanalysis techniques are particularly effective when the objective is to analyze two designs that share similar mesh structure, and stiffness matrices. Unfortunately, the process of 几何分析 can result in a dramatic change in the mesh structure and stiffness matrices, making reanalysis techniques less relevant.A related problem that is not addressed in this paper is that of localglobal analysis 13, where the objective is to solve the local field around the defeatured region after the global defeatured problem has been solved. An implicit assumption in localglobal analysis is that the feature being suppressed is self-equilibrating.3. Proposed methodology3.1. Problem statementWe restrict our attention in this paper to engineering problems involving a scalar field u governed by a generic 2nd order partial differential equation (PDE):A large class of engineering problems, such as thermal, fluid and magneto-static problems, may be reduced to the above form.As an illustrative example, consider a thermal problem over the 2-D heat-block assembly illustrated in Fig. 2.The assembly receives heat Q from a coil placed beneath the region identified as coil. A semiconductor device is seated at device. The two regions belong to and have the same material properties as the rest of . In the ensuing discussion, a quantity of particular interest will be the weighted temperature Tdevice within device (see Eq. (2) below). A slot, identified as slot in Fig. 2, will be suppressed, and its effect on Tdevice will be studied. The boundary of the slot will be denoted by slot while the rest of the boundary will be denoted by . The boundary temperature on is assumed to be zero. Two possible boundary conditions on slot are considered: (a) fixed heat source, i.e., (-krT).n = q, or (b) fixed temperature, i.e., T = Tslot. The two cases will lead to two different results for defeaturing induced error estimation.Fig. 2. A 2-D heat block assembly.Formally,let T (x, y) be the unknown temperature field and k the thermal conductivity. Then, the thermal problem may be stated through the Poisson equation 18:Given the field T (x, y), the quantity of interest is:where H(x, y) is some weighting kernel. Now consider the defeatured problem where the slot is suppressed prior to analysis, resulting in the simplified geometry illustrated in Fig. 3.Fig. 3. A defeatured 2-D heat block assembly.We now have a different boundary value problem, governing a different scalar field t (x, y):Observe that the slot boundary condition for t (x, y) has disappeared since the slot does not exist any morea crucial change!The problem addressed here is:Given tdevice and the field t (x, y), estimate Tdevice without explicitly solving Eq. (1).This is a non-trivial problem; to the best of our knowledge,it has not been addressed in the literature. In this paper, we will derive upper and lower bounds for Tdevice. These bounds are explicitly captured in Lemmas 3.4 and 3.6. For the remainder of this section, we will develop the essential concepts and theory to establish these two lemmas. It is worth noting that there are no restrictions placed on the location of the slot with respect to the device or the heat source, provided it does not overlap with either. The upper and lower bounds on Tdevice will however depend on their relative locations.3.2. Adjoint methodsThe first concept that we would need is that of adjoint formulation. The application of adjoint arguments towards differential and integral equations has a long and distinguished history 19,20, including its applications in control theory 21,shape optimization 22, topology optimization, etc.; see 23 for an overview.We summarize below concepts essential to this paper.Associated with the problem summarized by Eqs. (3) and (4), one can define an adjoint problem governing an adjoint variable denoted by t_(x, y) that must satisfy the following equation 23: (See Appendix A for the derivation.)The adjoint field t_(x, y) is essentially a sensitivity map of the desired quantity, namely the weighted device temperature to the applied heat source. Observe that solving the adjoint problem is only as complex as the primal problem; the governing equations are identical; such problems are called self-adjoint. Most engineering problems of practical interest are self-adjoint, making it easy to compute primal and adjoint fields without doubling the computational effort.For the defeatured problem on hand, the adjoint field plays a critical role as the following lemma summarizes:Lemma 3.1. The difference between the unknown and known device temperature, i.e., (Tdevice tdevice), can be reduced to the following boundary integral over the defeatured slot:Two points are worth noting in the above lemma:1. The integral only involves the slot boundary slot; this is encouraging perhaps, errors can be computed by processing information just over the feature being suppressed.2. The right hand side however involves the unknown field T (x, y) of the full-featured problem. In particular, the first term involves the difference in the normal gradients, i.e.,involves k(T t). n; this is a known quantity if Neumann boundary conditions kT . n are prescribed over the slot since kt. n can be evaluated, but unknown if Dirichlet conditions are prescribed. On the other hand,the second term involves the difference in the two fields,i.e., involves (T t); this is a known quantity if Dirichlet boundary conditions T are prescribed over the slot since t can be evaluated, but unknown if Neumann conditions are prescribed. Thus, in both cases,