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曲轴的加工工艺及夹具设计外文翻译

曲轴的加工工艺及夹具设计外文翻译
曲轴的加工工艺及夹具设计外文翻译

毕业设计

外文翻译

题目曲轴的加工工艺及夹具设计学院航海学院

专业轮机工程

学生佟宝诚

学号 10960123 指导教师彭中波

重庆交通大学

2014年

Proceedings of IMECE2008

2008 ASME International Mechanical Engineering Congress and Exposition

October 31-November 6, 2008, Boston, Massachusetts, USA

IMECE2008-67447

MULTI-OBJECTIVE SYSTEM OPTIMIZATION OF ENGINE CRANKSHAFTS USING

AN INTEGRATION APPROACH

Albert Albers/IPEK Institute of Product Development

University of Karlsruhe Germany

Noel Leon/CIDyT Center for Innovation andDesign

Monterrey Institute of Technology,Mexico

Humberto Aguayo/CIDyT Center forInnovation and Design,

Monterrey Institute ofTechnology, Mexico

Thomas Maier/IPEK Institute of Product Development

University of Karlsruhe Germany

ABSTRACT

The ever increasing computer capabilities allow faster analysis in the field of Computer Aided Design and Engineering (CAD & CAE). CAD and CAE systems are currently used in Parametric and Structural Optimization to find optimal topologies and shapes of given parts under certain conditions. This paper describes a general strategy to optimize the balance of a crankshaft, using CAD and CAE software integrated with Genetic Algorithms (GAs) via programming in Java. An introduction to the groundings of this strategy is made among different tools used for its implementation. The analyzed crankshaft is modeled in commercial parametric 3D CAD software. CAD is used for evaluating the fitness function (the balance) and to make geometric modifications. CAE is used for evaluating dynamic restrictions (the eigenfrequencies). A Java interface is programmed to link the CAD model to the CAE software and to the genetic algorithms. In order to make geometry modifications to

our case study, it was decided to substitute the profile of the counterweights with splines from its original “arc-shaped” design. The variation of the splined profile via control points results in an imbalance

response. The imbalance of the crankshaft was defined as an independent objective function during a first approach, followed by a Pareto optimization of the imbalance from both correction planes, plus the curvature of the profile of the counterweights as restrictions for material flow during forging. The natural frequency was considered as an additional objective function during a second approach. The optimization process runs fully automated and the CAD program is on hold waiting for new set of parameters to receive and process, saving computing time, which is otherwise lost during the repeated startup of the cad application.

The development of engine crankshafts is subject to a continuous evolution due to market pressures. Fast market developments push the increase of power, fuel economy, durability and reliability of combustion engines, and calls for reduction of size, weight, vibration and noise, cost, etc. Optimized engine components are therefore required if competitive designs must be attained. Due to this conditions, crankshafts, which are one of the most analyzed engine components, are required to be improved [1]. One of these improvements relies on material composition, as companies that develop combustion engines have expressed their intentions to change actual nodular steel crankshafts from their engines, to forged steel crankshafts. Another important direction of improvement is the optimization of its geometrical characteristics. In particular for this paper is the imbalance, first Eigen-frequency and the forge-ability. Analytical tools can greatly enhance the understanding of the physical phenomena associated with the mentioned characteristics and can be automated to do programmed tasks that an engineer requires for optimizing a design [2].The goals of the present research are: to construct a strategy for the development of engine crankshafts based on the integration of: CAD and CAE (Computer Aided Design &Engineering) software to model and evaluate functional

parameters, Genetic Algorithms as the optimization method, the use of splines for shape construction and Java language programming for integration of the systems. Structural optimization under these conditions allows computers to work in an

automated environment and the designer to speed up and improve the traditional design process. The specific requirements to be satisfied by the strategies are: Approach the target of imbalance of a V6 engine crankshaft, without affecting either its weight or its

manufacturability.

Develop interface programming that allows integration of the different software: CAD for modeling and geometric evaluations, CAE for simulation analysis and evaluation ,Genetic Algorithms for optimization and search for alternatives .

Obtain new design concepts for the shape of the counterweights that help the designer to develop a better crankshaft in terms of functionality more rapidly than with the use of a “manual” approach

Shape optimization with genetic algorithms

Genetic Algorithms (GAs) are adaptive heuristic search algorithms (stochastic search techniques) based on the ideas of evolutionary natural selection and genetics [3]. Shape optimization based on genetic algorithm (GA), or based on evolutionary algorithms (EA) in general, is a relatively new area of research. The foundations of GAs can be found in a few articles published before 1990 [4]. After 1995 a large number of articles about investigation and applications have been published, including a great amount of GA-based geometrical boundary shape optimization cases. The interest towards research in evolutionary shape optimization techniques has just started to grow, including one of the most promising areas for EA-based shape optimization applications: mechanical engineering. There are applications for shape determination during design of machine components and for optimization of functional performance of these the components, e.g. antennas [5], turbine blades [6], etc. In the ield of mechanical engineering, methods for structural and topological optimization based on evolutionary algorithms are used to obtain optimal geometric solutions that were commonly approached only by costly and time consuming iterative process. Some examples are the computer design and optimization of cam shapes for diesel engines [7]. In this case the objective of the cam design was to minimize the vibrations of the system and to make smooth changes to a splined profile.

In this article the shape optimization of a crankshaft is discussed, with focus on the geometrical development of the counterweights. The GAs are integrated with CAD and CAE systems that are currently used in Parametric and Structural Optimization to find optimal topologies and shapes of given

parts under certain conditions. Advanced CAD and CAE software have their own optimization capabilities, but are often limited to some local search algorithms, so it is decided to use genetic algorithms, such as those integrated in DAKOTA (Design Analysis Kit for Optimization Applications) [8] developed at Sandia Laboratories. DAKOTA is an optimization framework with the original goal of

providing a common set of optimization algorithms for engineers who need to solve structural and design problems, including Genetic Algorithms. In order to make such integration, it is necessary to develop an interface to link the GAs to the CAD models and to the CAE analysis. This paper presents an approach to this task an also some approaches that can be used to build up a strategy on crankshaft design anddevelopment.

Multi-objective considerations of crankshaft performance

The crankshaft can be considered an element from where different objective functions can be derived to form an optimization problem. They represent functionalities and restrictions that are analyzed with software tools during the design process. These objective function are to be optimized (minimized or maximized) by variation of the geometry. The selected goal of the crankshaft design is to reach the imbalance target and reducing its weight and/or increasing its first eigenfrequency. The design of the crankshaft is inherently a multiobjective optimization (MO) problem. The imbalance is measured in both sides of the crankshaft so the problem is to optimize the components of a vector-valued objective function consisting of both imbalances [9]. Unlike the single-objective optimization, the solution to this problem is not a single point, but a family of points known as the Pareto-optimal set. Each point in this set is optimal in the sense that no improvement can be achieved in one objective component that does not lead to degradation in at least one of the remaining components [10].

The objective functions of imbalance are also highly nonlinear. Auxiliary

information, like the derivatives of the objective function, is not available. The fitness-function is available only in the form of a computer model of the crankshaft, not in analytical form. Since in general our approach requires taking the objective function as a black box, and only the availability of the objective function value can be guaranteed, no further assumptions were considered. The Pareto-based optimization method, known as the Multiple Objective Genetic Algorithm (MOGA) [11], is used in the present MO problem, to finding the Pareto front among these two fitness functions.

In GA’s, the natural parameter se t of the optimization problem is coded as a

finite-length string. Traditionally, GA’s use binary numbers to represent such strings: a string has a finite length and each bit of a string can be either 0 or 1. By maintaining a population of solutions, GA’s c an search for many Pareto-optimal solutions in parallel. This characteristic makes GA’s very attractive for solving MO problems. The following two features are desired to solve MO problems successfully:

1) the solutions obtained are Pareto-optimal and

2) they are uniformly sampled from the Pareto-optimal set.

NOMENCLATURE

CAD: Computer Aided Design; GAs: Genetic Algorithms; EA: Evolutionary Algorithms; MO: Multi-objective; MOGA: Multi-objective Genetic Algorithm; CW: Counterweight; FEM: Finite Element Method.

OPTIMIZATION OF BALANCE WITH GEOMETRICAL

Fig. 1: Imbalance graph from the original crankshaft Design

Crankshaft shape parameterization

In order to make geometry modifications it is decided to substitute the current shape design of the crankshaft under analysis, from the original “arc-shaped” design representation of the counterweight’s profile, to a profile using spline curves

The figure 2 shows a counterweight profile of the crankshaft.

曲轴的加工工艺

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引进整条生产线的只有极少数厂家,如文登天润曲轴有限公司引进了德国KW铸造生产线。 2、钢曲轴毛坯的锻造技术 近几年来,国内已引进了一批先进的锻造设备,但由于数量少,加之模具制造技术和其他一些设施跟不上,使一部分先进设备未发挥应有的作用。从总体上来讲,需改造和更新的陈旧的普通锻造设备多,同时,落后的工艺和设备仍占据主导地位,先进技术有所应用但还不普遍。 3、机械加工技术 目前国内曲轴生产线多数由普通机床和专用机床组成,生产效率和自动化程度相对较低。粗加工设备多采用多刀车床车削曲轴主轴颈及拐颈,工序的质量稳定性差,容易产生较大的内应力,难以达到合理的加工余量。一般精加工采用MQ8260等曲轴磨床粗磨-半精磨-精磨-抛光,通常靠手工操作,加工质量不稳定。 随着贸易全球化的到来,各厂家已意识到了形势的严峻性,纷纷进行技术改造,全力提升企业的竞争力,近年来引进了许多先进设备和技术,进展速度很快。就目前状况来讲,这些设备和技术基本依赖进口。下面就哈尔滨东安动力、一汽大柴、文登天润曲轴、滨州海得曲轴等公司的情况作以介绍。 哈尔滨东安集团曲轴生产线为全自动柔性流水生产线,粗加工生产线由德国的专机自动线(LINDENMAIER)、数控车-车拉、数控高速随动外铣(BOEHRINGER)、圆角滚压机(HEGENSCHEIDT-MFD)和止推面车滚专机、淬火机(EMA)等组成;精加工生产线由日本的数控高速CBN磨床(TOYODA)、动平衡机、抛光机(IMPCO-NACHI)、检测机、清洗机等组成。连杆轴颈加工则采用了数控高速随动加工技术,全线采用高速CBN砂轮磨削技术,磨削线速度达到120m/s。 文登天润曲轴通过引进德、美、意等发达国家的先进设备,组建了具有当今国

(完整版)加工工艺毕业设计论文

优秀论文审核通过 未经允许切勿外传 毕业论文(设计)任务书 题目:曲轴的数控工艺分析与设计 成绩__________ 姓名陆国豪 班级10261 学号

设计日期:2012年5月 毕业论文(设计)任务书 题目:曲轴的数控工艺分析与设计 成绩__________ 姓名王磊 班级10261 学号

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The crankshaft is one of the key parts of the car engine, the performance of a direct influence on the automobile engine quality and life. The crankshaft engine for maximum load and all of the power, under the direction of the powerful changing bending moment and torque, and suffering from long time reciprocating linear motion through the connecting rod into the rotary motion, thus realize engine by chemical energy into mechanical energy output. 绪论 对轴类零件及夹具结构设前言计,不仅在加深我们对课程基本理论的理而且在加强对解决加工实际问题能力的方面有着很好的促进作用。可以让我们可以够将在湖北职业技术学院机电工程系两年所学知识融会贯通,也使我们在设计过程中不断学习一些新知识。通过毕业设计这个意义重大的课程,可以培养我们广泛查找资料、分析解决问题的能力,使我们养成严

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5、技术要求 6、工艺路线

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发动机曲轴加工工艺分析与毕业设计

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汽车发动机曲轴材料的选择及工艺设计

专业课程设计任务书 学生姓名:班级: 设计题目:汽车发动机曲轴材料的选择及工艺设计 设计内容: 1、根据零件工作原理,服役条件,提出机械性能要求和技术要求。 2、选材,并分析选材依据。 3、制订零件加工工艺路线,分析各热加工工序的作用。 4、制订热处理工艺卡,画出热处理工艺曲线,对各种热处理工艺进行分 析,并分析所得到的组织,说明组织及性能的检测方法与使用的仪器设备。 5、分析热处理过程中可能产生的缺陷及补救措施。 6、分析零件在使用过程中可能出现的失效方式及修复措施。

目录 0 前言 (1) 1 汽车发动机曲轴的工作条件及性能要求 (2) 1.1 汽车发动机曲轴的工作条件 (3) 1.2 汽车发动机曲轴的性能要求及技术要求 (3) 2 汽车发动机曲轴的材料选择及分析 (4) 2.1 零件材料选择的基本原则 (4) 2.2 曲轴常用材料简介 (5) 2.3 汽车发动机曲轴材料的确定 (5) 3 曲轴的加工工艺路线及热处理工艺的制定 (6) 3.1 35CrMo曲轴热处理要求 (6) 3.2 汽车曲轴的热处理工艺的制定 (6) 3.2.1 调质处理 (7) 3.2.2 去应力退火 (8) 3.2.3 圆角高频淬火和低温回火 (9) 4 曲轴热处理过程中可能产生的缺陷及预防措施 (11) 4.1 校直过程引起材料原始裂纹 (11) 4.2 曲轴圆角淬火不当引起裂纹源 (12) 4.3 淬火畸变与淬火裂纹 (12) 4.4 淬火导致氧化、脱碳、过热、过烧 (13) 4.5 淬火硬度不足 (13) 5 曲轴在使用过程中可能产生的失效形式及分析 (13) 6 课程设计的收获与体会 (14) 7 参考文献 (15) 8 工艺卡 (16)

夹具设计英文文献

A review and analysis of current computer-aided fixture design approaches Iain Boyle, Yiming Rong, David C. Brown Keywords: Computer-aided fixture design Fixture design Fixture planning Fixture verification Setup planning Unit design ABSTRACT A key characteristic of the modern market place is the consumer demand for variety. To respond effectively to this demand, manufacturers need to ensure that their manufacturing practices are sufficiently flexible to allow them to achieve rapid product development. Fixturing, which involves using fixtures to secure work pieces during machining so that they can be transformed into parts that meet required design specifications, is a significant contributing factor towards achieving manufacturing flexibility. To enable flexible fixturing, considerable levels of research effort have been devoted to supporting the process of fixture design through the development of computer-aided fixture design (CAFD) tools and approaches. This paper contains a review of these research efforts. Over seventy-five CAFD tools and approaches are reviewed in terms of the fixture design phases they support and the underlying technology upon which they are based. The primary conclusion of the review is that while significant advances have been made in supporting fixture design, there are primarily two research issues that require further effort. The first of these is that current CAFD research is segmented in nature and there remains a need to provide more cohesive fixture design support. Secondly, a greater focus is required on supporting the detailed design of a fixture’s physical structure. 2010 Elsevier Ltd. All rights reserved. Contents 1. Introduction (2) 2. Fixture design (2) 3. Current CAFD approaches (4) 3.1 Setup planning (4) 3.1.1 Approaches to setup planning (4) 3.2 Fixture planning (4) 3.2.1 Approaches to defining the fixturing requirement (6) 3.2.2 Approaches to non-optimized layout planning (6) 3.2.3 Approaches to layout planning optimization (6) 3.3 Unit design (7) 3.3.1 Approaches to conceptual unit design (7)

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