3532 提升机制动系统(液压盘式制动器)设计
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3532
提升机制动系统(液压盘式制动器)设计
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河南理工大学万方科技学院本科毕业设计（论文）中期检查表指导教师：张 跃 敏 职称： 副 教 授 所在系部（单位）：机械与动力工程系 教研室（研究室）： 题 目提升机制动系统的设计学生姓名高金涛专业班级08机制04班学号0828030014一、选题质量 1）该选题是提升机自动系统的设计，可以对我们大学四年所学知识进行一次全面的综合能力的练习，将对我们以后工作起到十分有效的帮助，加强了实际的动手动脑能力。题目的难易程度很适中，对我既是一个挑战也是一个很好的锻炼提高过程。 2）题目的工作量：要求完成3.5张A0图纸，50页左右设计说明书一份。二、开题报告完成情况 在指导老师和同学们的帮助之下，经过一番查阅资料，我顺利的开始了本次毕业设计。虽然我平常生活中经常听说有关提升绞车的各方面东西，但我对这方面的了解是明显的不够多。所以在刚开始不是很顺利，甚至无从入手。但经过指导老师的引导和在网上查找相关资料，我逐渐找到了设计的切入点，顺利得完成了开题报告。并有了一定的成果和进行了一些前期的工作，并使本次设计有了一个良好的开始。最后我在查阅了一些资料以后，现在已经进入了计算设计过程，我将在以后工作中继续努力，认真完成这次毕业设计。三、阶段性成果目前主要有以下成果：1、 掌握了提升机基本使用工况，特点2、 完成提升机的选型计算3、 完成提升机的制动装置的结构设计4、 完成提升机制动系统的可靠性评定四、存在主要问题由于之前没有接触过提升机制动系统设计，对涉及内容了解的不多，前期进展较为缓慢。之后通过大量的查阅资料，对提升机制动系统进行更深入的了解。对多种加工方法的学习、选择入手，并对车床进给系统重新进行了学习。在使用AutoCAD绘制图纸时，由于平常操作较少，熟练程度不高，绘制时间较长。五、指导教师对学生在毕业实习中，劳动、学习纪律及毕业设计（论文）进展等方面的评语指导教师： （签名） 年 月 日河南理工大学万方科技学院万方科技学院 本科毕业论文（英文翻译）院（系部） 机械与动力工程系 专业名称 机械设计制造及自动化 年级班级 2008级机制04班 学生名称 高 金 涛 指导老师 张 跃 敏 Reflections regarding uncertainty of measurement, on the results of a Nordic fatigue test interlaboratory comparisonMagnus Holmgren, Thomas Svensson, Erland Johnson, Klas JohanssonAbstract This paper presents the experiences of calculation and reporting uncertainty of measurement in fatigue testing. Six Nordic laboratories performed fatigue tests on steel specimens. The laboratories also reported their results concerning uncertainty of measurement and how they calculated it. The results show large differences in the way the uncertainties of measurement were calculated and reported. No laboratory included the most significant uncertainty source, bending stress (due to misalignment of the testing machine, “incorrect” specimens and/or incorrectly mounted specimens), when calculating the uncertainty of measurement. Several laboratories did not calculate the uncertainty of measurement in accordance with the Guide to the Expression of Uncertainty in Measurement (GUM) 1.Keyword Uncertainty of measurement, Calculation, Report, Fatigue test, Laboratory intercomparisonDefinitions R Stress ratio Fmin/Fmax F Force (nektons) A and B Fatigue strength parameters s and S Stress (megapascals) N Number of cycles. IntroductionThe correct or best method of calculating and reporting uncertainty of measurement in testing has been the subject of discussion for many years. The issue became even more relevant in connection with the introduction of ISO standards, e.g. ISO17025 2. The discussion, as well as implementation of the uncertainty of measurement concept, has often been concentrated on which equation to use or on administrative handling of the issue. There has been less interest in the technical problem and how to handle uncertainty of measurement in the actual experimental situation, and how to learn from the uncertainty of measurement calculation when improving the experimental technique. One reason for this may be that the accreditation bodies have concentrated on the very existence of uncertainty of measurement calculations for an accredited test method, instead of on whether the calculations are performed in a sound technical way. The present investigation emphasizes the need for a more technical focus. One testing area where it is difficult to do uncertainty of measurement calculations is fatigue testing. However, there is guidance on how to perform such calculations, e.g. in Refs. 3, 4. To investigate how uncertainty of measurement calculations are performed for fatigue tests in real life, UTMIS (the Swedish fatigue network) started an interlaboratory comparison where one of the most essential parts was to calculate and report the uncertainty of measurement of a typical fatigue test that could have been ordered by a customer of the participating laboratories. For cost reasons, customers often ask for a limited number of test specimens but, at the same time, they request a lot of information about a large portion of the possible stress-life area from few cycles (high stresses) to millions of cycles (low stresses) and even run-outs. The way the calculation was made should also be reported. The outcome concerning the uncertainty of measurement from the project is reported in this article. ParticipantsSix Nordic laboratories participated in the interlaboratory comparison: one industrial laboratory, two research institutes, two university laboratories and one laboratory in a consultancy company. Two of the laboratories are accredited for fatigue testing, and a third laboratory is accredited for other tests. Each participant was randomly assigned a number between 1 and 6, and this notification will be used in the rest of this paper. Experimental procedureThe participants received information about the test specimens (without material data), together with instructions on the way to perform the test and how to report the results.The instructions were that tests should be performed as constant load amplitude tests, with R=0.1 at three different stress levels, 460, 430 and 400 Map, with four specimens at each stress level, at a test frequency between 10 and 30 Hz, with a run-out limit at cycles and in a normal laboratory climate ( and relative humidity). This was considered as a typical customer ordered test.The test results were to be used to calculate estimates of the two fatigue strength parameters, A and B, according to linear regression of the logs and long variables, i.e. The reported result should include both the estimated parameters A and B and the uncertainties in them due to measurement errors. The report should also include the considerations and calculations behind the results, especially those concerning uncertainty of measurement.Several properties were to be reported for each specimen. The most important one was the number of cycles until fracture or if the specimen was a run-out (i.e. survived for cycles).The tests were to be performed in accordance with ASTM E-46696 5 and ISO5725-2 6. ASTM E-466-96 does not take uncertainty of measurement into account;However, ASTM E-466-96 mentions that the bending stress introduced owing to misalignment must not exceed 5% of the greater of the range, maximum or minimum stresses. There are also requirements for the accuracy of the dimensional measurement of the test specimen.All participants used hydraulic testing machines. The test specimens were made of steel (yield stress 375390 Map, and tensile strength 670690 Map, tabulated values). The test specimens were distributed to the participants by the organizer. ResultsThe primary laboratory results that should be compared are the estimated Whaler curves. In order to present all results in the same way, the organizer transformed some of the results. The Whaler curves reported by the participants are shown in Fig. 1.It can be seen that there are considerable differences between laboratories. An approximate statistical test shows a significant laboratory effect. Material scatter alone cannot explain the differences in the Whaler curves. In order to investigate if the laboratory effect was solely caused by the modeling uncertainty, we estimated new parameters from the raw data with a common algorithm. We then chose to use only the failed specimens and to make the minimization in the logarithmic life direction. The results are shown in Fig. 2. A formal statistical significance test was then made, and the result of such a test shows that the differences between the laboratories shown in Fig. 1 could be attributed only to modeling.Uncertainty of measurement calculationsOne of the most important objectives with this investigation was to compare the observed differences between laboratory test results with their estimated uncertainties of measurement. The intention was to analyze the uncertainty analyses as such, and to compare them to the standard procedure recommended in the ISO guide: Guide to the Expression of Uncertainty in Measurement (GUM) 1.The laboratories identified different sources of uncertainty and treated them in different ways. These sources are the load measurement, the load control, the superimposed bending stresses because of misalignment and the dimensional measurements. Implicitly, laboratory temperature and humidity, specimen temperature and corrosion effects are also considered. In addition, the results show a modeling effect. The different laboratory treatments of these sources are summarized in Table 1.Specific comments on the different laboratoriesAll laboratories gave their laboratory temperature and humidity, but did not consider these values as sources of uncertainty, i.e. the influence of temperature and humidity was neglected. This conclusion is reasonable for steel in the temperature range and humidity range in question 7.Laboratory 1. The uncertainty due to the applied stress was determined taking load cell and dimensional uncertainties into account. The mathematical evaluation was made in accordance with the GUM. Specimen temperature was measured, but was implicitly neglected. The modeling problem was mentioned, but not considered as an uncertainty source. Laboratory 2. The report contains no uncertainty evaluation. The uncertainties in the load cell and the micrometer are considered, but neglected with reference to the large material scatter. Specimen temperature was measured. Modeling problems are mentioned by a comment regarding the choice of load levels.Laboratory 3. The report contains no uncertainty evaluation. However, the accuracy of the machine is given and the load was controlled during the tests to be within specified limits. The bending stresses were measured on one specimen, but their influence on the fatigue result was not taken into consideration. Laboratory 4. The uncertainties in the load cell and the dimensional measurements are considered in an evaluation of stress uncertainty. The method for the evaluation is not in accordance with the GUM method, but was performed by adding absolute errors. The bending stress influence and the control system deviations are considered, but not included in the uncertainty evaluation. The failure criterion is mentioned and regarded as negligible, and corrosion is mentioned as a possible source of uncertainty. Laboratory 5. Uncertainties in the load cell and the load control were considered, and the laboratory stated in the report that the evaluation of the load uncertainty was performed according to the CIPM method. Laboratory 6. No report was provided, but only experimental results and a Whaler curve estimate.No laboratory reported the uncertainty in the estimated material properties, the Whaler parameters, but at most the uncertainty in the applied stress. The overall picture of the uncertainty considerations is that only uncertainty sources that are possible to estimate from calibration reports were taken into account in the final evaluation.Fig. 1 All experimental results and estimated Whole curves from the different laboratoriesNumber of cycles to failureOne important source that several laboratories mentioned is the bending stresses induced by misalignment in the testing machine, incorrectly mounted test specimens or “incorrect” specimens. The amount of bending stress was also estimated in some cases, but its influence on the uncertainty in the final Whole curve was not investigated.The results from this experimental investigation show that there are different ways of determining the Whole curve from the experimental result. One problem is the surviving specimens, the run-out results. Four laboratories used only the failed specimens results for the curve-fit, one laboratory neglected all results at the lowest level, and one laboratory included the run-outs in the estimation. Another problem is the mathematical procedure for estimating the curve. Common practice, and the recommendation in the ASTM standard, is that the curve should be estimated by minimizing the squared errors in log life, i.e. the statistical model is, (1)Where e is a random error, assumed to have constant variance, and where log stands for the logarithm with base 10. E can be interpreted as the combination of at least two types of errors: namely (1) a random error due to the scatter in the material properties, and (2) a measurement error due to uncertainties in the measurement procedures.Fig. 2 All experimental results and estimated Whole curves using the common procedureNumber of cycles to failureTable 1 Sources of uncertainty and laboratory treatmentC The laboratory report considers the source explicitly or implicitly, N the laboratory report neglects the source, A the laboratory report takes the source into account in the uncertainty of measurement calculationWhere e is a random error, assumed to have constant variance, and where log stands for the logarithm with base 10. E can be interpreted as the combination of at least two types of errors: namely (1) a random error due to the scatter in the material properties, and (2) a measurement error due to uncertainties in the measurement procedures. Stress was minimized, which led to a model discrepancy as discussed in the following.DiscussionExperimental resultsMost laboratories performed estimations of the Whaler curve parameters. Visual comparison of their estimated curves suggests differences, and a statistical test verified the conclusion that there is a statistically significant laboratory effect. A closer study of each participants procedure for determining the Whaler curve shows that the differences seem to be caused by different modeling of the curve.Since the test was intended to simulate a customer ordered test, some specific problems occurred. First, the number of test specimens is limited and therefore one should be careful when drawing conclusions from the results, since the scatter is considerable in fatigue and the number of specimens are limited.Another problem that occurred was that, since run-outs were wanted, two different failure criteria (failure mechanisms) were used to halt the test: fracture of the test specimen or cycles. In the latter case, the use of the equation may cause problems, see later.The investigator then looked at whether any laboratory differences remained after excluding the model interpretation effects. This was accomplished in two ways:Namely, firstly by direct comparison of the experimental fatigue lives obtained, and secondly by using the same estimating procedure on all data sets. This therefore tested whether any laboratory differences remained or not. The first comparison was done on the two higher load levels. For these, no statistically significant differences were found. The second comparison, which included the failuresOn the lowest level, verified the result. Since the variation between laboratories is larger than the variation within a laboratory no statistically significant variation within a laboratory can be distinguished from the totalVariation in material.The conclusion is that no systematic errors in measurements were detected, but different modeling techniques give significant differences in the results. This in fact indicates that when different fitting models are used different quantities are measured even though they have the same name. Before any agreement is reached about the way of reporting fatigue data, it is of utmost importance that the modeling procedure is clearly defined in the test report. It is very important for the laboratories customers to be aware of this fact and, when requesting a test, to ask for a preferred modeling procedure as well as to be aware of the modeling procedure used by the laboratory when using fatigue data in design.Uncertainty evaluationAll laboratories made some considerations regarding the uncertainties of measurement. However, none of them evaluated uncertainties for the resulting Whole parameters, but only for the applied stress. However, none of the measurement uncertainties reported are unrealistic considering the factors taken into account, this is based inexperience. Since the specimens were destroyed during the tests it is not possible to separate the material variation from the repeatability. An estimate of the combined measurement uncertainty and the variation in material isAbout 30% of the lifetime and the major contribution are from the material variation and therefore one conclusion is that the measurement uncertainty in this test could be neglected during this test. This is not true for all fatigue tests and it is therefore anyhow interesting to study how the participants treated measurement uncertainty.Only one participant used the method recommended by the ISO guide GUM. This is surprising, since European accreditation authorities have recommended the GUM for several years. Among the uncertainty sources that were identified by the laboratories, only load cell measurement uncertainties and dimensional measurement uncertainties were taken into account. Important sources such as misalignment and load control were identified by some participants but were not included in the evaluation of stress uncertainty. Apparently only calibrated devices were considered for the overall uncertainty, and other sources, more difficult to evaluate, were excluded. No motivation for these exclusions can be found in the reports. One participant rejected the uncertainty evaluation with reference to the large scatter in fatigue lives. Our overall conclusion from the laboratory comparisons, that there are no detectable systematic effects, may be seen as verification of this rejection, but it is questionable if this was an obvious result beforehand. In contrast, for instance, uncertainties due to misalignment are not obviously negligible in comparison with the material scatter, and should be considered in an uncertainty analysis. This investigation, together with other observations 8, 9, shows problems with the introduction of the ISO17025 requirement for uncertainty of measurement statements. The reasons for this may be that the uncertainty of measurement discussion during recent years has concentrated very much on which equation to use and on administrative aspects, e.g. whether the uncertainty of measurement should always be reported directly in the report, or only when the customer requests it, etc., instead of on the real technical issues. Hopefully, the introduction of the pragmatic ILAC-G17:2002, a document about the introduction of the concept of uncertainty of measurement in association with testing 10, will improve the situation. ConclusionsThe way to define, calculate, and interpret uncertainty of measurement and to use it in Whaler-curve determination is poorly understood among the participants, in spite of the fact that they consist of a group with significant experienceOf fatigue testing, and that some of them were also accredited for fatigue tests. An important overall tendency is that the laboratories only include uncertaintySources that are easily obtained, e.g. from calibrated gauges where calibration certificates exist.关于北欧的疲劳实验室的比较测量结果不确定值的反映摘要：这篇论文介绍了关于疲劳检测的不确定性的计算和报告的实验。6个北欧实验室对钢性元件进行了疲劳实验，他们也报告了疲劳测量不确定性的结果和计算方法。实验结果表明大量的测量不确定性结果是可以计算和报告的。没有实验室包括最重要的不确定源，当它们进行不确定值的计算时，有几个实验室没有计算符合从指导到结果的测量的不确定性值。关键词：测量，计算，不确定性报告，疲劳测试，联合实验室介绍：计算和报告测量的不确定性值的最好或者正确的方法一直是许多年来讨论的问题,随着ISO(例如ISO17025)的引进这个问题更加突出。关于测量的不确定性值的讨论和鉴定与这个问题息息相关。在发展实验技术的时候已经有很少人对技术问题和在实验条件下如何处理测量的不确定性值和如何从测量的不确定性值可以学到什么感兴趣了。这种现象可能的一个原因是合格的物体已经集中在用精确的方法计算测量的不确定性值上，而不是集中在用这种方法是不是合理的问题上了。目前的方法集中在一种更加科学的方法上。对测量的不确定性值计算比较困难的一个领域是疲劳测量。但是，对于这样的计算有一个指导，研究如何确定测量不确定性值的方法是研究现实生活中物体的疲劳检测。瑞典疲劳网站开设了一家联合实验室公司，它的最重要的一部分就是计算和报告重要疲劳实验的不确定性值，这些实验是由实验室的参与者进行的。最重要的原因是顾客们索要有限个测量模型，同时，他们也需要大量的信息。所用的计算方法也要报告，关于工程测量的不确定性值的结果也在这篇文章中报告。 六个北欧的实验室都参加了这个联合实验室，一个工业实验室，两个研究院，两个大学实验室，一个咨询公司实验室。其中两个实验室研究疲劳实验，第三个研究其他的实验，每个参与者被随意指派16的编号，这个报告被用在这篇文章的其他部分。实验程序： 参与者收到了没有数据的材料模型，及其如何进行测量和如何报告结果的信息。要求是在固定载荷下进行多次实验，用半径为1mm的在三种压力（460，430，400MP）下，每种压力下都进行试验的4种模型，频率在10-30Hz之间，在室温下旋转5百万转。这就是客户要求的测量。 这种测量结果被用来计算两个物体的疲劳增长的参数，A和B,和由于测量错误而引起的不确定性值，报告的结果应该包括A和B的结果和这种不确定性值，在结果的后面尤其是这些不确定性值每个模型的这几种特性都应该报告。最重要的是模型达到疲劳时的周期数，或者是模型报废的周期数。做这个测量时ASTM E-466-96、ISO-5725-2.、ASTM E-466-96并没有考虑到测量的不确定性值，由于误差不能超过最大和最小值的范围的百分之五，所以，ASTM-466-96参照弯曲压力，对模型的测量也有一些精度要求。所有的参加者都用液压疲劳机，测量模型是由钢制成的，它的表面的压力范围是375-390Mp,拉伸力压强的范围是670-690Mp.测量模型由组织者分发给参加者。结果：为了用同一种方法表示出所有的结果，初级实验结果应该用Whole表格来进行比较，参与者报告的Whole表格见图1。它显示了各实验室之间的显著的差别。一个大概统计的实验结果表明了各实验室的显著差别，分散的材料不能单独解释Whole表格的区别，为了研究各实验室的差别是否是因为模型的不确定造成的，我们比较了由原始数据得出的新数据，当我们使用那些不合格的模型时，对结果进行对数运算后，结果如2图所示。以前的统计结果和这次的结果比较可得结果如图1所示。测量计算得不确定性这个研究的重要过程之一就是比较各实验室之间的估计的测量不确定性的差别。目的就是分析测量的不确定性，参照ISO标准比较他们的制造水平，各实验室把不同的不确定性集中起来用不同的方法来处理。由于误差和空间的测量，这些资源是固定的测量，确定的控制和可靠的弯曲应力，而且，实验室内的温度和湿度，模型的温度和腐蚀的影响也需要考虑。结果也表明了模型制造的效果。不同的实验室对这些材料的处理方法如图1所示。不同实验室的具体评论所有的实验室都设定了室内温度和湿度，但是他们没有把它们看成是误差的因素。比如，他们忽视了温度和湿度的影响，对于钢来说，这种结论在室内温度和湿度下是合理的。 实验室1：不确定性值是由于所用的压力把承载单元和空间不确定性值也考虑了进去。数学公式是根据GUM来计算的，模型的温度可以测量，但是它们很容易被忽视。模型问题虽然考虑到了，但是并没有被认为是不确定性的源泉。实验室2：报告并没有包括不确定性的值，载荷单元的不确定性值和微小误差被考虑了，但是忽视了大的分散的材料，模型温度被测量了，模型制造方法也被考虑到了，
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