专用机床多轴箱的可靠性分析【中文3216字】
收藏
资源目录
压缩包内文档预览：
编号：10346002
类型：共享资源
大小：767.89KB
格式：ZIP
上传时间：2018-08-02
上传人：闰***
认证信息
个人认证
冯**（实名认证）
河南
IP属地：河南
15
积分
- 关 键 词：
-
专用
机床
轴箱
可靠性分析
中文
- 资源描述：
-
专用机床多轴箱的可靠性分析【中文3216字】,专用,机床,轴箱,可靠性分析,中文
- 内容简介：
-
International Journal of Science Vol.3 No.5 2016 ISSN: 1813-4890 194 Reliability Analysis on Multi-Axle Box of Dedicated Machine Qingchen Li, Yinghua Liao, Fengjiang Li School of Mechanical Engineering, Sichuan University of Science reliability; Monte Carlo method; ANSYS 1. Introduction In a dedicated machine tool, the box is one of the most important parts of the multi axle box. The axles, bearings, bearing covers and other parts of multi axle box are respectively arranged on the box through different installation forms. The box also fixes the whole multi axle box on the machine tool bed by its own structure. The box not only transmits the force and torque between part with part, part with machined workpiece in the multi axle box, but also plays an important role in ensuring the position accuracy of each rotating axle and the relative position accuracy between rotating axle with machine tools guide rail. The box will deform under the action of external force, its deformation will directly affect the position accuracy of the parts in the multi axle box, and then affect the accuracy and reliability of the entire multi axle box. If the deformation of the box is too large, beyond the allowable range, it may causes the failure of the multi axle box12. The finite element analysis of the deformation of the box is usually based on the certainty parameters, that is to say, the material properties, boundary conditions, loads and other parameters are all assured. However, there are many uncertainties in these parameters, which brings some new problems to the deterministic finite element analysis. On the one hand, with the development of the finite element technology, a lot of high precision elements are put forward, which makes the calculation accuracy more and more high. On the other hand, there is a large statistical randomness in the material parameters, boundary conditions and loads, which makes the high precision of the high precision element greatly reduced due to the influence of the statistical randomness. In order to solve this problem, it is necessary to regard the material properties, loads and other uncertain factors as random variables, the carries on reliability probability analysis of box3. In this paper, the box of a dedicated machine tools drilling multi axle box is taken as an example, the reliability of the box is studied by using the finite element software ANSYS. International Journal of Science Vol.3 No.5 2016 ISSN: 1813-4890 195 2. Reliability analysis theory For the case of the multi axle boxs box, its reliability means the probability of completing the specified function under the prescribed conditions and the prescribed time interval. Its failure can be considered that the maximum deformation is more than the allowable deformation, which leads to the processing precision is not required. Failure probability Pf can be expressed as: 0)( 0)(0)( xgf dXxfxgPP (1) In the formula, g(x) is the structures function under limit state, the random variables X=(X1,X2,Xn) in it express random parameters. When g(x)0, the box is in safe condition. When g(x)=0, the box is in the limit state. When g(x)0, the box is fail. Generally, it is difficult to directly establish the expression of f(x). In ANSYS, the reliability of the box can be studied by Monte Carlo method45. Monte Carlo simulation methods basic idea as follows: Firstly, builds a stochastic model which is corresponding to the researched object, forms a random variable and its digital feature (such as probability, expectation. etc). Then in order to get plenty of random variables sample value, a great deal of random experiments had been done. Lastly, calculates the digital features estimative figure by using the statistic feature. Based on this idea, set the object function Z=g(X1,X2,X n), among them Xi is random variable, it subjects to a certain distribution. Takes N times random sampling for X, gets N groups of sample. Then substitutes the value of j group into the object function, gets the value of Zj (j=1,2,n). If there are Nj groups of N which made Zj0, the probability of structural failure is: NNP ff (2) In the formula, N is the total number of samples, Nf is the number of failure. 3. Steps of reliability analysis 3.1 Build the model of box Before using ANSYS to study the reliability of the box, we must first establish the structure model of the box, the structural models quality will affect the efficiency and accuracy of the finite element analysis to a large extent6. Because the ANSYS modeling operation is very complicated, so this paper uses the three-dimensional modeling software Proe to carry on the modeling to the box, then imports the model into ANSYS. The fillet, chamfer, screw holes and other small structure will be divided into many elements when analyze in ANSYS, which will greatly increase the analysis time. The results of the finite element analysis will not produce large changes after ignoring these small features. So, in the process of building structure model, the box is simplified properly. The simplified box includes the subject box and box cover two parts. The model of subject box is shown in figure 1, the model of box cover is shown in figure 2. Figure 1 Model of subject box International Journal of Science Vol.3 No.5 2016 ISSN: 1813-4890 196 Because the subject box and the box cover are connected by screws, there will not be relative sliding produced between them, so the two parts of the box are regarded as an integral part of the finite element analysis. The model of box is shown in figure 3. Figure 2 Model of box cover Figure 3 Box model of multi axle box 3.2 Perform reliability analysis When using ANSYS reliability analysis module Prob Design to carry on the reliability analysis to the box body, the following three steps are included: generating analysis file, performing reliability analysis and dealing with results7. (1) Generating analysis file. Analysis file refers to the cyclic document of the reliability analysis, it needs to be written by ANSYS parametric design language APDL. The rationality of the analysis file is an important guarantee for reliability analysiss calculation efficiency and correctness of the results. The creation of analysis file contains pretreatment, solving and extraction results 3 parts. The first step is to pre-treat the box: first, the box model is introduced, and the element type is SOLID185, the material parameter E=1.4e11, the Poissons ratio is 0.25, the density is 7300N/m3. Then meshing the model (the element level is set to level 3). The finite element analysis model of the box is shown in Figure 4. International Journal of Science Vol.3 No.5 2016 ISSN: 1813-4890 197 Figure 4 Finite element analysis model of box The second step is to solve, sets full constraints to the contact surface of box and machine tool bed, sets cutting force F=663.8N, and then solves by the Solver. The third step is to extract the results, extracts the maximum deformation of the box, sets to the parameter of U. (2) Performing reliability analysis. After entering the analysis file, you need to repeat the analysis file to achieve reliability analysis, this is the key link of reliability analysis. This stage mainly includes: the definition of input and output variables, the choice of analysis method, the implementation of the reliability cycle 3 steps. Whether static or dynamic analysis, the material is regarded as the ideal material, and its parameters are in good accordance with the theoretical value. But in reality, there is a small difference between the materials, the material parameters can not be absolutely the same. In addition, due to the external conditions such as temperature and other factors such as cutting tool, workpiece, the size of the cutting force is also changing. So, you can specify the modulus of elasticity of the material, the density and the cutting force as random input variables, its parameters are shown in Table 1. Table 1 Random parameters Distribution type Mean value Standard deviation Modulus of elasticity E(Pa) GAUSS 1.4E11 1.4E9 Density (N/m3) GAUSS 7300 100 Cutting force F(N) GAUSS 663.8 20 Next, sets the maximum deformation of the box as the output variable U. Then selects Latin Hypecube of Monte Carlo as analysis method to sample 500 times, Performs reliability analysis. (3) Dealing with results. When cycle completed, you can view the input and output variables sampling value, histogram and probability cumulative curve. 4. Reliability analysiss results of the box The three input variables statistical histograms are shown in Figure 5, 6 and 7 International Journal of Science Vol.3 No.5 2016 ISSN: 1813-4890 198 Figure 5 Histogram of elastic modulus E Figure 6 Histogram of density Figure 7 Histogram of cutting load F In the figure, the horizontal coordinate indicates the value of each random variable, and the longitudinal coordinate is the relative frequency (the proportion that a values sample number for the International Journal of Science Vol.3 No.5 2016 ISSN: 1813-4890 199 total sample number). The red line is the curve that fits the frequency of each value. It can be seen from the statistical histogram that the curves of the 3 random variables are very smooth, and the shape conforms to the characteristic of GAUSS distribution, it means the sample number 500 times is sufficient. The value of each input variable is shown in Table 2 Table 2 Value feature of input parameters Mean value Standard deviation Maximum value Minimum value Modulus of elasticity E(Pa) 1.4e11 1.398e9 1.44e11 1.357e11 Density (Kg/m3) 7299.9 99.86 7589.3 6990.3 Cutting force F(N) 663.81 20.06 731.25 605.56 It can be seen from the table that each parameters value is very similar to the preset value, it means the value is reasonable and reliable. Sets the confidence probability to 95%, we can get the output variables sampling, histogram and probability cumulative curve as shown in Figure 8, 9 and 10. 1 .2 0 E - 61 .3 0 E - 61 .4 0 E - 6U1 .3 5 E - 61 .2 5 E - 6Figure 8 Sampling of output parameter U 1 .2 2 8 E - 61 .3 5 6 E - 61 .2 5 9 E - 6 1 .2 8 9 E - 6 1 .3 2 0 E - 6UFigure 9 Histogram of output parameter U International Journal of Science Vol.3 No.5 2016 ISSN: 1813-4890 200 1 .2 0 E - 6 1 .3 5 E - 61 .2 3 E - 6 1 .2 6 E - 6 1 .2 9 E - 6 1 .3 2 E - 6Figure 10 Probability cumulative curve of output parameter U It can be seen from the figure that when the modulus of elasticity, density, and the value of the cutting force is no longer constant, the maximum deformation of the box U is no longer fixed, but approximate GAUSS distribution, mean value is about 1.289310-6mm, standard deviation is about 2.143610-8mm. In addition, we can continue to calculate the reliability of the box under a certain deformation according to the probability cumulative curve. As shown in Table 3, the reliability of the box under some typical allowable deformation is given. Table 3 Reliability of box under typical allowable deformations Allowable deformation(mm) 1.25e-6 1.3e-6 1.35e-6 Reliability 43.04% 69.83% 99.76% Conversely, we can also calculate the allowable deformation under a certain reliability. For example, in order to ensure the reliability of the box is not less than 98%, the boxs allowable deformation can not be less than 1.335e-6mm. In the process of practical design and optimization, it is supposed not only to know which factors may affect the deformation, but also to understand the sensitivity of these factors to the deformation, then to determine the primary and secondary relationships to consider various factors of optimal design. Through the reliability analysis of ANSYS, these data can be clearly obtained. The sensitivity of the modulus of elasticity, density and cutting force to the deformation is shown in Figure 11. Figure 11 Sensitivity distribution map of parameters International Journal of Science Vol.3 No.5 2016 ISSN: 1813-4890 201 It can be seen that in the three factors, the density of the material is the most important factor that affects the deformation of the box, followed by the modulus of elasticity, and cutting forces effect is very small. The reason for this phenomenon is that the variation range of cutting force F is small. 5. Conclusion (1) When the modulus of elasticity, the density and the cutting force are used as the random input variables, the boxs maximum deformation U is no longer fixed, but approximate GAUSS distribution, mean value is about 1.289310-6mm, standard deviation is about 2.143610-8mm. (2) The reliability of the box under allowable deformations 1.3510-6mm is 99.76%. Conversely, in order to ensure the reliability of the box is not less than 98%, the boxs allowable deformation can not be less than 1.335e-6mm. (3) In the three factors, the density of the material is the most important factor that affects the deformation of the box, followed by the modulus of elasticity, and cutting forces effect is very small. It is because the variation range of cutting force F is small. Acknowledgements This article is supported by the Innovation Fund of Postgraduate, Sichuan University of Science & Engineering (No. y2014035) and the Science and Technology Bureau of Zigong City (No. 2013J19) and Sichuan University of Science & Engineering (No. 2014PY04). References 1 Molodova M, Li Z, Dollevoet R. Axle box acceleration: Measurement and simulation for detection of short track defectsJ. Wear, 2011, 271(1): 349-356. 2 Lee J S, Choi S, Kim S S, et al. A mixed filtering approach for track condition monitoring using accelerometers on the axle box and bogieJ. Instrumentation and Measurement, IEEE Transactions on, 2012, 61(3): 749-758. 3 Der Kiureghian A, Ke J B. The stochastic finite element method in structural reliabilityJ. Probabilistic Engineering Mechanics, 1988, 3(2): 83-91. 4 Zhiyu Sun, Liangyu Chen. The Design Theory and Method of mechanical Reliability M. Beijing: Science Press, 2003. 5 Zhang Q L, Pei U. Random finite element analysis for stochastical responses of structures J. Computer & structures, 1997, 62(4): 611-616. 6 Lee Huihuang. Finite Element Simulation with ANSYS WorkbenchM. Taiwan, Schroff Development Corp,2010. 7 Chen Puhui, Xiao Shanshan. Probabilistic Design Methodology for Composite Aircraft J. Journal of Nanjing University of Aeronautics and Astronautics. 2012, 44(5): 683-693 【中文 3216字】International Journal of Science Vol.3 No.5 2016 ISSN: 1813-4890 专用机床多轴箱的可靠性分析Qingchen Li, Yinghua Liao, Fengjiang Li 四川理工大学机械工程学院，中国自贡 643000摘要：在专用机床中，箱体是多轴箱最重要的部件之一，其变形将直接影响多轴箱中部件的位置精度，从而影响整个多轴箱的精度和可靠性。箱体变形的有限元分析通常基于某些参数。考虑到实际中弹性模量，密度和切削力的随机性，在有限元分析软件 ANSYS 中建立了箱体的有限元模型，弹性模量，密度和切割力被认为是随机输入变量，最大变形被认为是输出变量，采用蒙特卡罗方法分析箱体的可靠性，并获得箱体允许变形的可靠性。提供了一种可行的分析方法，用于箱子和类似零件的可靠性设计。关键词：箱子； 可靠性；蒙特卡罗方法；ANSYS1、前言：在专用的机床中，箱体是多轴箱最重要的部件之一。多轴箱的轴，轴承，轴承盖等部件分别通过不同的安装形式安装在箱体上。该箱还通过其自身的结构将整个多轴箱固定在机床上。该箱不仅在多轴箱内部分与加工件之间传递力和扭矩，而且在确保每个旋转轴的位置精度以及旋转轴与机床导轨的相对位置精度之间起着重要的作用。箱体在外力作用下会变形，其变形将直接影响多轴箱内部件的位置精度，影响整个多轴箱的精度和可靠性。如果箱体的变形太大，超出允许范围，则可能导致多轴箱的故障。箱体变形的有限元分析通常基于确定性参数，也就是说，材料性质，边界条件，载荷等参数都是有保证的。然而，这些参数存在许多不确定性，这对确定性有限元分析带来了一些新的问题。 一方面，随着有限元技术的发展，提出了很多高精度元件，使计算精度越来越高。另一方面，材料参数，边界条件和载荷具有较大的统计随机性，这使得由于统计随机性的影响，高精度元件的高精度大大降低。为了解决这个问题，有必要将材料性质，载荷等不确定因素作为随机变量，进行箱子的可靠性概率分析3。在本文中，以专用机床钻多轴箱为例，使用有限元软件 ANSYS 对箱体的可靠性进行了研究。2、可靠性分析理论对于多轴箱箱体的情况，其可靠性意味着在规定的条件和规定的时间间隔内完成指定功能的概率。可以认为其失效最大变形大于允许变形，这样就不需要加工精度。故障概率 Pf可表示为：（1）0xgf dXfP在公式中，g（x）是极限状态下的结构函数，其中随机变量 X =（X1，X2 ，. Xn）表示随机参数。当 g（x） 0 时，箱子处于安全状态。当 g（x）= 0 时，箱子处于极限状态。当 g（x）0 时，箱子失败。通常，很难直接建立 f（x）的表达式。在 ANSYS 中，盒子的可靠性可以通过蒙特卡罗方法进行研究。蒙特卡罗模拟方法的基本思想如下：首先构建一个与研究对象相对应的随机模型，形成随机变量及其数字特征（如概率，期望等）。然后要做大量的随机实验以获得大量随机变量的样本值。最后，使用统计特征来计算数字特征的估计值。基于这个想法，设置对象函数 Z = g（X1，X2 ，. Xn ），其中 Xi 是随机变量，它遵循一定的分布。对 X进行 N 次随机抽样，得到 N 组样本。然后将 j 组的值代入对象函数，得到 Zj（j = 1,2，. n）的值。如果 N 中有 Nj 组使 Zj 0，结构失效的概率为：（2）Pff在公式中，N 是样本总数，Nf 是失败次数。3.可靠性分析步骤3.1 建立箱子模型在使用 ANSYS 研究箱体的可靠性之前，首先必须建立箱体的结构模型，结构模型的质量将在很大程度上影响有限元分析的效率和精度。因为 ANSYS 建模操作非常复杂，所以本文使用三维建模软件 Proe 对框进行建模，然后将模型导入 ANSYS。在 ANSYS 中分析时，圆角，倒角，螺孔等小结构将分为多个要素，大大增加了分析时间。有限元分析的结果在忽略这些小特征之后不会产生很大的变化。所以在建筑结构模型的过程中，箱子被简化了。简化箱包括主题箱和箱盖两部分。主题箱的模型如图 1 所示，箱盖的型号如图 2 所示。由于主体箱和箱盖通过螺丝连接，因此它们之间不会产生相对滑动，因此箱子的两个部分被认为是有限元分析的组成部分。箱型号如图 3 所示。图 1：主题箱模型图 2：箱盖模型图 3：多轴箱的箱模型3.2 进行可靠性分析当使用 ANSYS 可靠性分析模块 Prob Design 对箱体进行可靠性分析时，包括以下三个步骤：生成分析文件，执行可靠性分析和处理结果。（1）生成分析文件。分析文件是指循环文件的可靠性分析，需要用 ANSYS 编写的参数设计语言APDL。分析文件的合理性是可靠性分析计算效率和结果正确性的重要保证。分析文件的创建包含预处理，求解和提取结果 3 部分。第一步是对箱子进行预处理：首先引入箱型，元件类型为 SOLID185，材料参数 E = 1.4e11，泊松比为0.25，密度为 7300N / m3。然后网格化模型（元素级别设置为级别 3）。箱体的有限元
- 温馨提示:
1: 本站所有资源如无特殊说明，都需要本地电脑安装OFFICE2007和PDF阅读器。图纸软件为CAD,CAXA,PROE,UG,SolidWorks等.压缩文件请下载最新的WinRAR软件解压。
2: 本站的文档不包含任何第三方提供的附件图纸等，如果需要附件，请联系上传者。文件的所有权益归上传用户所有。
3.本站RAR压缩包中若带图纸，网页内容里面会有图纸预览，若没有图纸预览就没有图纸。
4. 未经权益所有人同意不得将文件中的内容挪作商业或盈利用途。
5. 人人文库网仅提供信息存储空间，仅对用户上传内容的表现方式做保护处理，对用户上传分享的文档内容本身不做任何修改或编辑，并不能对任何下载内容负责。
6. 下载文件中如有侵权或不适当内容，请与我们联系，我们立即纠正。
7. 本站不保证下载资源的准确性、安全性和完整性, 同时也不承担用户因使用这些下载资源对自己和他人造成任何形式的伤害或损失。
人人文库网所有资源均是用户自行上传分享，仅供网友学习交流，未经上传用户书面授权，请勿作他用。
川公网安备: 51019002004831号