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旋转式水稻钵苗移栽机构的设计
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目 录
摘 要2
Abstract2
第一章 绪论7
1.1 本文研究目的与意义7
1.2 水稻钵苗移栽机构的发展概况8
1.2.1 国外发展概况8
1.2.2 国内发展概况10
1.3 研究目标与方案实现13
1.3.1 研究目标14
1.3.2 实现方案14
1.4 本文的工作安排16
1.5本章小结17
第二章 旋转式水稻钵苗移栽机构的运动学分析18
2.1 旋转式水稻钵苗移栽机构的工作原理18
2.2 运动学分析符号及相关说明19
2.3 椭圆齿轮－不完全非圆齿轮传动特性分析20
2.3.1 椭圆齿轮－不完全非圆齿轮节曲线模型建立20
2.3.2 传动比分析24
2.4 椭圆齿轮传动特性分析27
2.4.1 椭圆齿轮节曲线模型建立27
2.4.2 传动比分析28
2.5 椭圆-不完全非圆齿轮行星轮系移栽机构运动学模型的建立29
2.5.1 位移方程29
2.5.2 速度分析31
2.5.3 加速度分析32
2.6 本章小结32
第三章 旋转式水稻钵苗移栽机构辅助分析与优化软件的运用34
3.1 优化软件的运用思路34
3.2 旋转式水稻钵苗移栽机构的优化软件界面35
3.3 数据处理36
3.4 本章小结37
第四章 旋转式水稻钵苗移栽机构的结构设计38
4.1旋转式水稻钵苗移栽机构的整体结构设计38
4.2 驱动部分设计40
4.2.1 非匀速间歇传动机构的设计40
4.2.2 非匀速传动机构的设计41
4.3 移栽臂组成零件的设计41
4.3.1拨叉的设计42
4.3.2推秧爪与弹簧片的设计43
4.4 本章小结44
第五章 旋转式水稻钵苗移栽机构的三维建模45
5.1椭圆齿轮与非圆齿轮的实体建模45
5.1.1椭圆齿轮的三维建模45
5.1.2非圆齿轮的三维建模46
5.2 其他零部件的三维建模47
5.3本章小结47
第六章 总结48
6.1 总结48
参考文献49
摘 要
水稻钵苗移栽是一种利用钵盘育秧的水稻移栽技术，是水稻种植过程中的重要环节。水稻的钵盘育秧充分保留了秧苗生长的营养土质，植伤轻、返苗快，使作物提早成熟，且增产增收；移栽充分利用了光热资源，对水稻秧苗有气候的补偿作用，同时有使作物生育提早的综合效益，因此水稻的钵苗移栽可以产生非常可观的经济效益和社会效益。但与其他国家和地区相比，我国水稻种植机械化程度较低，与国内水稻生产的其它环节相比，机械化程度也是最低的。因此研究一种新的水稻钵苗移载机构，对水稻的机械化种植与高产高收具有非常重要的意义。
本文通过对国内外的水稻钵苗移栽机构进行对比分析，提出了一种高效率的水稻钵苗移栽机构为旋转式水稻钵苗移栽机构。该水稻钵苗移栽机构由驱动部分与移栽臂两部分构成，其中驱动部分由非匀速间歇传动机构与非匀速传动机构串联组成，移栽臂用于完成机构的取秧、推秧。
本文的研究内容如下：
1.根据水稻钵苗移栽的农艺特性与工作轨迹的要求，确定了以椭圆－不完全非圆齿轮行星轮系为传动机构的设计方案，该旋转式传动机构平稳性好、效率高。
2.分析了该水稻钵苗移栽机构的工作原理，并对机构进行运动学建模与传动特性分析。
3通过水稻钵苗移栽机构的辅助分析与优化软件，对该机构进行参数优化，最后得到一组较优的结构参数：a=23.069mm，k=0.994，α=291°，λ=6°，δ=29°，φ0=-39°，S=152mm.
4.根据机构优化后的结构参数，在CAD2008软件中对水稻钵苗移栽机构进行整体的结构设计与各零部件的二维设计。
5.在ug8.0三维实体建模软件中完成各零部件的建模与机构的装配。
关键词：水稻钵苗移栽；行星系移栽机构；椭圆－不完全非圆齿轮；参数优化；设计；
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外 文 翻 译班级：学号：姓名:指导教师：Pitting failure of truck spiral bevel gearAbstractSpiral bevel gears are some of the most important elements used in truck differential. In this study, the fracture of spiral bevel gear for truck differential produced from case hardening steel is investigated. In order to study the causes of the failure,specimens prepared from the damaged spiral bevel gears were subjected to experiments, such as visual inspection,hardness, chemical analysis and metallurgical tests. Pitting occurrence on gear surfaces was observed. The effect of microstructure on the fracture was considered. Low surface hardness values were found. The calculated contact stress was higher than the allowable contact stress which is emphasized in literature.1. IntroductionDifferential drives are packaged units used for a wide range of power-transmission applications. The spiral bevel gears are beginning to supersede straight-bevel gears in differential drives. They have curved oblique teeth that contact each other gradually and smoothly from one end of the tooth to the other, meshing with a rolling contact similar to helical gears (Fig. 1). They have the advantage of ensuring evenly distributed tooth loads and carry more loads without surface fatigue. Thrust loading depends on the direction of rotation and whether the spiral angle of the teeth is positive or negative 1,2. The investigated spiral bevel gears are made of two different case hardening steel. The case hardening steel (20MnCr5, EN10084) has a low carbonchromium and the other steel (17NiCrMo6-4, EN10084) has a low nickelchromiummolybdenum with medium hardenability, generally supplied in the as rolled condition with a maximum brinell hardness of 280 (30 HRC). It is characterized by good core strength and toughness in small to medium sections with case hardness up to 62 HRC when carburized, hardened and tempered. These steels can also be used (uncarburized) as high tensile steel, which when suitably hardened and tempered can be utilized for various applications requiring good tensile strength and reasonable toughness. Almost three gears are damaged every month in truck service. Therefore, the damaged spiral bevel gears of truck were evaluated, and the causes of fracture of a gear manufactured from case hardening steel were carried out. Some properties of truck differential are given in Table 1. Also, the main dimensions of the gears are shown in Fig. 2. A number of mechanical and microstructure analyses are carried out to determine the causes of fracture.2. Techniques used in fracture analysisFrom one point of view, causes of gear failure may include a design error, an application error, or a manufacturing error. Design errors include such factors as improper gear geometry as well as the wrong materials, quality levels, lubrication systems, or other specifications. Application errors can be caused by a number of problems, including mounting and installation, vibration, cooling, lubrication, and maintenance. Manufacturing errors may show up in the field as errors in machining or heat treating 3. In this analysis, the four damaged spiral bevel gear specimens were subjected to various tests. The following experimental works and stress calculations were done: visual inspection and fractography; hardness tests; chemical analysis; metallographic analysis; contact stress calculation.3. Analysis and results3.1. Visual inspection and fractographyThe investigated gears are shown in Fig. 3. The failed gears showed similar failure and did bear indication of fatigue crack growth when the fracture surface was examined, indicating that the failure was of a brittle type of fracture. The pitting on gear teeth surfaces assisted the failure. Pitting is caused by excessive surface stress due to high normal loads, a high local temperature due to high rubbing speeds, or inadequate lubricant. The pitting occurrence and the fractured surfaces of gears are shown in Fig. 4. According to the fractured surfaces, it was said that the failure was due to pitting.3.2. Hardness analysisCase-hardened gears are hardened only on the surface of the gear teeth, to a predetermined depth, to about 58 to 62 Rockwell C, or roughly as hard as a bearing race. The increased hardness improves the gears durability rating by providing greater resistance to pitting and greater strength, or resistance tobreakage 46. Hardness analysis of fractured gear materials was carried out using a Rockwell hardness test machine. The measurements were carried out on three different surface areas. The core and surface hardness values are given in Tables 2 and 3. Core hardness over 40 HRC is not recommended due to potential for distortion, residual stresses, and brittleness but the gear 1 core hardness value is higher than the recommended values. The surface hardness of gears was observed as 5054 HRC which is lower than the values stated in the literature.3.3. Chemical analysisChemical analyses of 20MnCr5 and 17NiCrMo6-4 case hardening steels according to EN 10084 are shown in Table 4. The chemical composition of the piston materials was determined by spectroscopy chemical analysis. The chemical compositions of gear material are listed in Table 5. It was understood from the chemical composition that the material was case hardening steel. The gear 1 is 17NiCrMo6-4 and 2, 3 and 4 are 20MnCr5. The composition of gear materials contains low C and Cr, Ni and Mo content, which cause the structure to quench in a tough mode. The alloying additions improve the hardenability of the steel. Chromium improves corrosion resistance, while manganese contributes to deoxidation of the melt and also improves machinability. Nickel reduces distortion and cracking upon quenching.3.4. Metallographic analysisThe metallographic specimens were first ground, polished and etched using standard techniques in order to examine the inner structure. A light optical microscope was used in the investigations. It can be understood from the figures that the gears were carburized and then cooled in the oil ambient. The microstructures of the failed gear materials show that they are similar structures. From the observation, it is concluded that the case hardening process was not properly done. Also, because of the application of improper heat treatment, gears core structure have a wholly martensite which is depicted Fig. 5. The core structure should be tough in gears not martensite and brittle.3.5. Stress calculationSince the pitting occurrence was observed at visual inspection, the contact stress on gear teeth was calculated.The stress experienced by the spiral bevel tooth during operation was estimated using the design torque of 250 Nm. The contact stress on the loaded tooth can be calculated using the equation 7。The terms used in equation are explained in Table 6. Using Eq. (1) and Table 6, the contact stress was calculated to be 1994 MPa. According to literature 6,7, allowable contact stress is 1550 MPa. This value is lower than the calculated value. In this case, gears have about 0.77 safety factors and they have not contact strength. Thus, the pitting failure was observed on gear teeth surface. The occurring pits have contributed tothe failure of gears.4. ConclusionIn this research, the influences of microstructure, chemical composition and hardness of the gears were investigated and contact stress was calculated. From the experimental observations and calculations, the following conclusions may be made:1. In order to obtain same hardness and microstructure, the gear materials should be of same chemical composition.2. The surface hardness of gears is low. In order to obtain maximum pitting resistance, the gears outer surface hardness should be increased to 5860 HRC.3. In order to obtain different microstructure between core and surface, carburising heat treatment should be made proper conditions, such as time, case depth. The case depth should be under control.4. Due to the high tooth-contact pressures, oil film thickness may not be enough. The lubrication could be difficult. Therefore, the pitting occurrence increases. On the examination of fractured parts, it can be concluded that the gears expose to overloading. In order to decreasing contact pressure, the gears geometry can be optimized in design stage or the pinion design torque can be decreased. 卡车螺旋锥齿轮的点蚀故障摘要： 螺旋锥齿轮是卡车差动齿轮中的重要组成部分。在这个研究当中，对因表面硬化钢齿轮而导致卡车差动齿轮中锥齿轮的断裂进行了调查。为了研究引起失效的原因，专家们从损坏的锥齿轮样品中进行实验，如外观检查，硬度、化学分析和冶金测试。齿轮表面的点蚀是可以被观察到的。微观结构的效应在断裂中被考虑了进去。低表面硬度的价值被发现。被计算的接触应力高于可允许的接触应力是这篇文章介绍的重点。1、 介绍 差分驱动器广泛应用于动力传输的单元。螺旋锥齿轮开始在差分驱动器中优于直锥齿轮。它们有弯曲的斜齿，并且逐渐接触从一端过渡到另一端，啮合的螺旋齿轮类似于滚动接触。它们的优点是确保负载均匀的分布在齿上，从而使其携带更多的载荷且不发生表面疲劳。推力载荷取决于旋转的方向和螺旋角的正负，调查的螺旋锥齿轮是由俩种不同的表面硬化钢构成的，表面硬化钢（20MnCr5,EN10084)具有低的碳-铬元素，其他钢（17NiCrMo6-4,EN10084)具有低的镍-铬-钼元素和中等的淬透性，在一般的轧制条件下，供给的最大布氏硬度为280（30HRC）。它的特点是在经过渗碳、淬火和回火后，中型材表面硬度提升至62HRC时，可以承受较高的应力并且具有较小的韧性。这些钢（非渗碳）也可用于作为高强度钢，并且通过适当的淬火和回火后，产生较好的拉伸强度和韧性，可满足多种应用。卡车运行的每个月中大约都有三个齿轮损坏。因此，对卡车中受损的螺旋锥齿轮进行了评估，并且分析了表面硬化钢制造的齿轮断裂的原因。2、 断裂分析中应用的技术 从企业的角度来说，齿轮发生故障的原因可能有设计错误、程序错误或者制造错误。设计错误包括齿轮几何形状不当，材料不当，质量水平不够或是润滑系统不完善。程序错误包括安装、振动、冷却和维护多个因素构成。制造错误可能会发生在现场的热处理或是作业中的不当处理。 在这个分析中，四个损坏的螺旋锥齿轮样本进行各种实验。进行的实验以及测量结果如下： 1、外观和断口检验 2、硬度实验 3、化学分析 4、金相分析 5、接触应力的计算3、 分析方法和结果 3.1 外观和断口检验 在图3所示调查的齿轮中。失效的齿轮都表现出了类似的故 障，对疲劳裂纹扩展的断裂面进行了检查，表明故障时脆性的折断。齿牙上的表面点蚀促进了齿轮的失效。点蚀是由于过多的表面承受高载荷，由于过高的摩擦速度导致局部温度过高，或是不充分润滑导致的。示于图4的齿轮发生点蚀的断裂表面，通过其断面表面，可以说是由于点蚀导致的。 3.2 硬度分析 表面硬化的齿轮的硬化只发生在齿轮表面，达到预定深度，达到58到62洛氏温度。通过增加硬度来提高齿轮的耐用性可以通过增加抗点蚀能力和提高耐断裂强度来达到。使用洛氏硬度试验机对断裂的齿轮材料进行了硬度分析，进行了三个不同表面区域的测量。其芯部和表面的硬度值分别在表2和表3中给出。由于潜在的失真，剩余应力和脆性，硬度高于40HRC的材料是不推荐的，但是齿轮1的硬度值是高于推荐值的。被观察到的50-54HRC表面硬度的材料是低于文献中所提到的数值的。 3.3 化学分析 对表面材料20MnCr5和17NiCrMo6-4的齿轮进行化学分析，通过EN10084在表4中给出。由光谱化学分析确定材料的化学组成。齿轮材料的化学成分在表5中给出。通过观察该材料的化学成分，确定该材料为硬化钢。齿轮1的材料为17NiCrMo6-4，齿轮2、3和4的材料为20MnCr5。齿轮材料的化学成分含有量较低的C和Cr,Ni和Mo元素，通过急速冷却后可形成特定的结构。合金添加剂可以提高钢的淬透性。铬可以提高耐腐蚀性，而锰有助于脱氧的熔融，同时提高了可加工性。镍减少淬火开裂后的变形。3.4 金相分析 失效的齿轮材料有着相类似的结构。从观察中可以得到结论。该情况下，硬化过程不完全。此外由于热处理应用不当，齿轮材料中的马氏体在图5中呈现。3.5 应力计算 通过可视观察齿轮的点蚀，发生在轮齿上的接触应力是可以被计算的。在对螺旋锥齿轮试验中，对齿轮附加扭矩为250NM。对于附加在轮齿上的接触应力可以由公式7计算。表6中有对该公式的术语解释。使用公式1和表6可以计算出接触应力为1994MPa。通过文本给出，可允许的接触应力为1550MPa。此值低于计算给出的数值。在这种情况下，齿轮大概有0.77安全系数且没有达到其接触强度。因此，在轮齿表面上可观察到点蚀现象。点蚀的发生是齿轮失效的原因。4、 总结 在这次的实验中，微观结构、化学组成和齿轮硬度被考虑了进来，同时计算出接触应力。从实验观测和应力计算中，得出以下结论：1、 为了获得相同的硬度和微观结构，齿轮材料应该有相同的化 学组成。2、 齿轮表面硬度过低。为了获得最大的耐腐蚀性，齿轮的表面 硬度应提高至58-60HRC。3、 为了获得不同的芯部和表面组织，渗碳热处理应给出适当的 条件，如时间、硬化层深度等等，深度应在控制之下。4、 由于高的齿接触压力，可能达不到足够的油膜厚度。润滑可 能非常困难，导致点蚀发生增加。通过裂隙部位的检查，可 以得出结论，齿轮承受重载荷。为了降低接触应力，可以对 齿轮的几何形状进行优化。在设计阶段中，小齿轮的设计可 以降低扭矩。 Engineering failure analysis Abstract The scale and complexity of computer-based safety critical systems, like those used in the transport and manufacturing industries, pose significant challenges for failure analysis.Over the last decade, research has focused on automating this task. In one approach, predictive models of system failure are constructed from the topology of the system and local component failure models using a process of composition. An alternative approach employs model-checking of state automata to study the effects of failure and verify system safety properties. In this paper, we discuss these two approaches to failure analysis. We then focus on Hierarchically Performed Hazard Origin & Propagation Studies (HiP-HOPS) one of the more advanced compositional approaches and discuss its capabilities for automatic synthesis of fault trees, combinatorial Failure Modes and Effects Analyses, and reliability versus cost optimisation of systems via application of automatic model transformations.We summarise these contributions and demonstrate the application of HiP-HOPS on a simplified fuel oil system for a ship engine. In light of this example, we discuss strengths and limitations of the method in relation to other state-of-the-art techniques. In particular,because HiP-HOPS is deductive in nature, relating system failures back to their causes, it is less prone to combinatorial explosion and can more readily be iterated. For this reason, it enables exhaustive assessment of combinations of failures and design optimisation using computationally expensive meta-heuristics.1. IntroductionIncreasing complexity in the design of modern engineering systems challenges the applicability of rule-based design andclassical safety and reliability analysis techniques. As new technologies introduce complex failure modes, classical manualanalysis of systems becomes increasingly difficult and error prone.To address these difficulties, we have developed a computerised tool called HiP-HOPS (Hierarchically Performed Hazard Origin & Propagation Studies) that simplifies aspects of the engineering and analysis process. The central capability of this tool is the automatic synthesis of Fault Trees and Failure Modes and Effects Analyses (FMEAs) by interpreting reusable specifications of component failure in the context of a system model. The analysis is largely automated,requiring only the initial component failure data to be provided, therefore reducing the manual effort required to examine safety; at the same time,the underlying algorithms can scale up to analyse complex systems relatively quickly, enabling the analysis of systems that would otherwise require partial or fragmented manual analyses.More recently, we have extended the above concept to solve a design optimisation problem: reliability versus cost optimisation via selection and replication of components and alternative subsystem architectures. HiP-HOPS employs genetic algorithms to evolve initial non-optimal designs into new designs that better achieve reliability requirements with minimal cost. By selecting different component implementations with different reliability and cost characteristics, or substituting alternative subsystem architectures with more robust patterns of failure behaviour, many solutions from a large design space can be explored and evaluated quickly. Our hope is that these capabilities, used in conjunction with computer-aided design and modelling tools, allow HiP-HOPS to facilitate the useful integration of a largely automated and simplified form of safety and reliability analysis in the context of an improved design process. This in turn will, we hope, address the broader issue of how to make safety a more controlled facet of the design so as to enable early detection of potential hazards and to direct the design of preventative measures. The utilisation of the approach and tools has been shown to be beneficial in case studies on engineering systems in the shipping 1 and offshore industries 2. This paper outlines these safety analysis and reliability optimisation technologies and their application in an advanced and largely automated engineering process. 2. Safety analysis and reliability optimisation3. Safety analysis using HiP-HOPSHiP-HOPS is a compositional safety analysis tool that takes a set of local component failure data, which describes how output failures of those components are generated from combinations of internal failure modes and deviations received at the components inputs, and then synthesises fault trees that reflect the propagation of failures throughout the whole system.From those fault trees, it can generate both qualitative and quantitative results as well as a multiple failure mode FMEA35.A HiP-HOPS study of a system design typically has three main phases: Modelling phase: system modelling & failure annotation. Synthesis phase: fault tree synthesis. Analysis phase: fault tree analysis & FMEA synthesis.Although the first phase remains primarily manual in nature, the other phases are fully automated. The general process inHiP-HOPS is illustrated in Fig. 2 below: The first phase system modelling & failure annotation consists of developing a model of the system (including hydraulic, electrical or electronic, mechanical systems, as well as conceptual block and data flow diagrams) and then annotating the components in that model with failure data. This phase is carried out using an external modelling tool or package compatible with HiP-HOPS. HiP-HOPS has interfaces to a number of different modelling tools, including Matlab Simulink, Eclipse-based UML tools, and particularly SimulationX. The latter is an engineering modelling & simulation tool developed by ITI GmbH36 with a fully integrated interface to HiP-HOPS. This has the advantage that existing system models, or at least models that would have been developed anyway in the course of the design process, can also be re-used for safety analysis purposes rather than having to develop a new model specific to safety. The second phase is the fault tree synthesis process. In this phase, HiP-HOPS automatically traces the paths of failure propagation through the model by combining the local failure data for individual components and subsystems. The result is a network of interconnected fault trees defining the relationships between failures of system outputs and their root causes in the failure modes of individual components. It is a deductive process, working backwards from the system outputs to determine which components caused those failures and in what logical combinations.The final phase involves the analysis of those fault trees and the generation of an FMEA. The fault trees are first minimised to obtain the minimal cut sets the smallest possible combinations of failures capable of causing any given system failure and these are then used as the basis of both quantitative analysis (to determine the probability of a system failure) and the FMEA, which directly relates individual component failures to their effects on the rest of the system. The FMEA takes the form of a table indicating which system failures are caused by each component failure.The various phases of a HiP-HOPS safety analysis will now be described in more detail.4. Design optimisation using HiP-HOPSHiP-HOPS analysis may show that safety, reliability and cost requirements have been met, in which case the proposed system design can be realised. In practice, though, this analysis will often indicate that certain requirements cannot be met by the current design, in which case the design will need to be revised.This is a problem commonly encountered in the design of reliable or safety critical systems. Designers of such systems usually have to achieve certain levels of safety and reliability while working within cost constraints. Design is a creative exercise that relies on the technical skills of the design team and also on experience and lessons learnt from successful earlier projects, and thus the bulk of design workis creative. However, we believe that further automation can assist the process of iterating the design by aiding in the selection of alternative components or subsystem architectures as well as in the replication of components in the model, all of which may be required to ensure that the system ultimately meets its safety and reliability requirements with minimal cost.A higher degree of reliability and safety can often be achieved by using a more reliable and expensive component, analternative subsystem design (e.g. A primary/standby architecture), or by using replicated components or subsystems to achieve redundancy and therefore ensure that functions are still provided when components or subsystems fail. In a typicalsystem design, however, there are many options for substitution and replication at different places in the system and differentlevels of the design hierarchy. It may be possible, for example, to achieve the same reliability by substituting two sensorsin one place and three actuators in another, or by replicating a single controller or control subsystem, etc. Different solutions will, however, lead to different costs, and the goal is not only to meet the safety goals and cost constraints but also to do so optimally, i.e. find designs with maximum possible reliability for the minimum possible cost. Because the options for replication and/or substitution in a non-trivial design are typically too many to consider manually, it is virtually impossible for designers to address this problem systematically; as a result, they must rely on intuition, or on evaluation of a few different design options. This means that many other options some of which are potentially superior are neglected. Automation of this process could therefore be highly useful in evaluating a lot more potential design alternatives much faster than a designer could do so manually. Recent extensions to HiP-HOPS have made this possible by allowing design optimisation to take place automatically 38.HiP-HOPS is now capable of employing genetic algorithms in order to progressively evolve” an initial design model thatdoes not meet requirements into a design where components and subsystem architectures have been selected and where redundancy has been allocated in a way that minimizes cost while achieving given safety and reliability requirements. In the course of the evolutionary process, the genetic algorithm typically generates populations of candidate designs which employ user-defined alternative implementations for components and subsystems as well as standard replication strategies.These strategies are based on widely used fault tolerant schemes such as hot or cold standbys and n-modular redundancy with majority voting. For the algorithm to progress towards an optimal solution, a selection process is applied in which the fittest designs survive and their genetic makeup is passed to the next generation of candidate designs. The fitness of each design relies on cost and reliability. To calculate fitness, therefore, we need methods to automatically calculate those two elements. An indication of the cost of a system can be calculated as the sum of the costs of its components (although for more accurate calculations,life-cycle costs should also be taken into account, e.g. production, assembly and maintenance costs) 39. However, while calculation of cost is relatively easy to automate, the automation of the evaluation of safety or reliability is more difficult as conventional methods rely on manual construction of the reliability model (e.g. the fault tree, reliability block diagram or the FMEA). HiP-HOPS, by contrast, already automates the development and calculation of the reliability model, and therefore facilitates the evaluation of fitness as a function of reliability (or safety). This in turn enables a selection process through which the genetic algorithm can progress towards an optimal solution which can achieve the required safety and reliability at minimal cost. One issue with genetic algorithms is that it has to be possible to represent the individuals in the population in this case,the design candidates as genetic encodings in order to facilitate crossover and mutation. Typically this is done by assigning integers to different alternatives in specific positions in the encoding string, e.g. a system consisting of three componentsmay be represented by an encoding string of three digits, the value of each of which represents one possible implementationfor those components. However, although this is sufficient if the model has a fixed, flat topology, it is rather inflexible andcannot easily handle systems with subsystems, replaceable sub-architectures, and replication of components, since thiswould also require changing the number of digits in the encoding string.The solution used in HiP-HOPS is to employ a tree encoding, which is a hierarchical rather than linear encoding that can more accurately represent the hierarchical structure of the system model. Each element of the encoding string is not simply just a number with a fixed set of different values, it can also represent another tree encoding itself. Fig. 7 shows these different possibilities: we may wish to allow component A to be replaced with either a low cost, low reliability implementation (represented as 1), a high cost, high reliability implementation (2), or an entirely new subsystem with a primary/standby configuration (3). If the third implementation is selected, then a new sub-encoding is used, which may contain further values for the components that make up the new subsystem, i.e. the primary and the standby.Thus encoding 1” means that the first implementation was chosen, encoding 2” means the second was chosen, 3(11)”means that the third was chosen (the subsystem) and furthermore that the two subcomponents both use implementation 1,while 3(21)” for example means that the primary component in the subsystem uses implementation 2 instead. Although the tree encoding is more complex, it is also much more flexible and allows a far greater range of configuration optionsto be used during the optimisation process.HiP-HOPS uses a variant of the NSGA-II algorithm for optimisation. The original NSGA-II algorithm allows for both undominated and dominated solutions to exist in the population (i.e. the current set of design candidates). To help decide which solutions pass on their characteristics to the next generation, they are ranked according to the number of other solutions they dominate. The more dominant solutions are more likely to be used than the less dominant solutions. HiP-HOPS is also able to discard all but the dominant solutions. This is known as a pure-elitist algorithm (since all but the best solutions are discarded) and also helps to improve performance.To further enhance the quality of solutions and the speed with which they can be found, a number of other modifications were made. One improvement was to maintain a solution archive similar to those maintained by tabu search and ant colony optimisation; this has the benefit of ensuring that good solutions are not accidentally lost during subsequent generations. Another improvement was to allow constraints to be taken into account during the optimisation process, similar to the way the penalty-based optimisation functions: the algorithm is encouraged to maintain solutions within the constraints and solutions outside, while permitted, are penalised to a varying degree. In addition, younger solutions i.e. ones more recently created are preferred over ones that have been maintained in the population for a longer period; again, this helps to ensure a broader search of the design space by encouraging new solutions to be created rather than reusing existing ones.工程故障分析摘要像在交通运输业和制造业中，使用的基于计算机安全的系统的规模和复杂性，对工程故障分析带来了重大的挑战。在过去的十年中，这个任务主要由自动化来完成。有一种系统故障模型是从系统的拓扑结构和本地使用过程中的组成构件来预测故障的模式。另一种方法是采用自动检查状态的模型来研究失效的影响，并验证系统的安全性能。在本文中，我们将讨论俩种方法失效分析。然后，我们专注于分级研究危险的起源和传播（HIP-HOPS）一个更先进的构图方法故障树，其功能可以自动合成，组合失效模式后果分析，可靠性和成本，系统通过自动模式transformations.We的应用来优化总结这些特点，并通过简化船舶发动机的燃油系统来证明HIP-HOPS在其中的应用。根据这个例子，我们讨论了与其他国家先进技术相比较，这种方法的优势和局限性。特别是由于HIP-HOPS能够演绎，可以归结出系统故障的原因，并且不容易发生组合爆炸，更容易的进行迭代。出于这个原因，它成为对故障和优化设计进行评估的启发式算法。1、 介绍现代工程系统的日益复杂对以规则为基础的设计，经典的安全性和可靠性分析技术的实用性提出了挑战。随着新技术的引入和复杂的故障模式，经典的系统分析变得越来越困难并且错误百出。我们已经开发出一种计算机工具，称为HIP-HOPS（分层分析危险来源），用于简化工程设计和分析过程。这个工具的核心在于自动分析故障树，以及重复分析系统模式内部的失效单元的FMEAs。分析是自动的，只需要初始的组件故障数据，因此，减少了手工安全检查，在相同的时间内，可扩展的底层算法可以相对快速的分析复杂的系统，也可以进行碎片式的故障分析。最近，我们通过选择和复制的组件和替代子系统架构，来解决一个优化设计问题：可靠性和成本优化。HIP-HOPS从引进遗传算法得出非最优方案进化到以小成本获得高的可能性的新设计。通过选择不同的组件实现不同的可靠性和成本特征，或用子系统替代架构，具有更强大的功能，可以解决许多方案，从大的空间探索到快速评估。我们希望在HIP-HOPS下，计算机辅助设计和建模工具能够结合使用，用于进行高度自动化和简化集成的安全性和可靠性分析并且改进设计过程。反
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