复杂曲面零件五轴加工刀轴整体优化方法

 针对复杂曲面零件五轴加工中刀轴矢量变化剧烈、严重影响工件表面加工质量的问题,提出一种基于临界约束的五轴刀轴矢量整体优化方法。首先,构造了给定切触点处所有可行摆刀平面,并在摆刀平面内根据临界约束计算出临界刀轴矢量,在获得临界刀轴矢量的基础上,对其进行平面映射,建立了刀轴摆动的初始可行域;其次,通过对初始可行域进行均匀离散,根据离散点之间相对位置关系构造邻接矩阵,并结合最短路径搜索算法获得了初始参考刀轴,从而构造了新的刀轴摆动可行域;最后,建立当前切削行内无干涉且相邻刀轴变化最小的刀轴矢量优化模型,实现自由曲面五轴加工无干涉刀轴矢量的光滑控制。两种自由曲面叶轮的加工算例分析表明,采用本文方法获得的刀轴矢量可以明显改善机床的运动性能,避免了刀具干涉的产生,可提高复杂曲面零件的加工质量与效率。     

Stochastic structural optimization using particle swarm optimization, surrogate models and Bayesian statistics

This paper focuses on a method to solve structural optimization problems using particle swarm optimization (PSO), surrogate models and Bayesian statistics. PSO is a random/stochastic search algorithm designed to find the global optimum. However, PSO needs many evaluations compared to gradient-based optimization. This means PSO increases the analysis costs of structural optimization. One of the methods to reduce computing costs in stochastic optimization is to use approximation techniques. In this work, surrogate models are used, including the response surface method (RSM) and Kriging. When surrogate models are used, there are some errors between exact values and approximated values. These errors decrease the reliability of the optimum values and discard the realistic approximation of using surrogate models. In this paper, Bayesian statistics is used to obtain more reliable results. To verify and confirm the efficiency of the proposed method using surrogate models and Bayesian statistics for stochastic structural optimization, two numerical examples are optimized, and the optimization of a hub sleeve is demonstrated as a practical problem.     

基于GB/T 24734的三维自动标注

结合制造企业对三维CAD零件尺寸自动标注的需求,探讨了以国标GB/T 24734为依据的在CAD系统中实现三维尺寸自动标注的技术.设计并实现了三维自动标注的算法,详细阐述了其相关的技术.该算法涉及零件基准识别、特征简化、表面分组、垂向投影标注以及零件特征还原等一系列技术.其中,特征简化和还原主要涉及特征和草图级别的倒角、圆角及阵列操作.为了便于尺寸的布局和识别,采用了表面分组和垂向投影标注的方法来对零件进行分解.以CAXA实体设计软件为平台,实现了上述算法,开发了自动标注模块,并验证了算法的可行性.     

A new structural reliability analysis method in presence of mixed uncertainty variables

For structures with both random and fuzzy uncertainty, this paper presents a novel method for determining the membership function in fuzzy reliability with the Automatic Updating Extreme Response Surface (AUERS) method. In the proposed method, fuzzy variables are initially converted into a value domain under the given cut level and the extreme point in the domain where the reliability reaches its extreme value is considered. Second, the Particle Swarm Optimization (PSO) algorithm is used to determine the extreme point according to the extreme responses for different sets of random sample inputs. A kriging response surface is subsequently constructed between the random variables and the corresponding extreme points. An automatic updating strategy is then introduced based on the Relative Mean Square Predicted Error (RMSPE) before performing every iteration of reliability analysis. By adding new sample points, the approximate quality of the kriging response surface is improved. Finally, reliability analysis is used to determine the reliability bound under the given cut level. The proposed method assures the accuracy and computation efficiency of the mixed uncertainty reliability analysis results while it prevents the solution from becoming trapped in a local optimum, which occurs in classical optimization methods. Two example analyses are used to demonstrate the validity and advantages of the proposed method.     

Simulation of multi-axis grinding considering runout based on envelope theory

As one of the most important methods for machining process with high accuracy, ultra-precision grinding is widely used in fields such as aerospace, automotive and mold, etc. Simultaneously, it is common that wheel and spindle axis do not coincide with each other due to wheel settings, machining errors and so on. This could result in the generation of wheel runout, which may reduce the machining surface’s quality. In this paper, combining this phenomenon, an analytic algorithm method for the multi-axis grinding process is introduced according to the envelope theory. After that, the accuracy of this method is verified. Two experiments are carried out on a 5-axis machining center. The artificial runout is set up and calculated utilizing the least square method. Finally, using the presented method, two examples with and without runout are introduced to illustrate the validation of the proposed model. The error due to the runout effect is also analyzed.     

Exploiting the Sentinel-3 tandem phase dataset and azimuth oversampling to better characterize the sensitivity of SAR altimeter sea surface height to long ocean waves

Being the very first SAR mode altimeter tandem phase, the Sentinel-3 A/B tandem phase has provided an unprecedented opportunity to better characterize the sensitivity of SAR altimetry retrievals to high-frequency processes, such as long ocean waves. In this paper, we show that for some sea-state conditions, that are still to be precisely characterized, long ocean waves are responsible for high-frequency (spatial and temporal) coherent Sea Level Anomaly (SLA) signals. It is found that the peak wavelength corresponds to the dominant swell wavelength. Furthermore, the short time lag between S3-A and S3-B acquisitions allows performing cross-spectral analyses that reveal phase shifts consistent with waves travelling according to the wave dispersion relation. It is also demonstrated that the classical 20 Hz sampling frequency is insufficient to properly sample most swell-induced SLA signals and that aliasing can generate errors over the entire frequency spectrum, including at long wavelengths. These results advocate for the use of azimuth oversampling (40 Hz or 80 Hz). Low-pass filtering should be applied prior to any down-sampling to 20 Hz, in order to prevent long-wavelength errors induced by spectral leakage.     

Sealing reliability modeling of aviation seal based on interval uncertainty method and multidimensional response surface

Many variables affect the sealing performance, and their distribution characteristics are difficult to obtain with probabilistic methods owing to the high cost involved. Numerous problems in engineering are similar due to the appearance of small-sample parameters. In this study, the sealing reliability of an aviation seal was defined as the research object, and an interval uncertainty method and multidimensional response surface were proposed to calculate the sealing reliability.Based on this, we first analyzed the failure mechanism of the aviation seal and established a leakage rate model. Then, based on the non-probabilistic interval model, an interval uncertainty method was proposed to construct the analytical model. With reference to the limit state equation from the structural reliability theory, the multidimensional response surface was used for fast calculation.Then, we chose the single-cylinder gas steering gear used in aircraft as the case study, its sealing reliability in working and non-working statuses were calculated, and the results were verified with the actual maintenance records. By analyzing the sensitivity of some variables, we can improve the sealing reliability of the aviation seal by improving the surface roughness only if the cost allows.Finally, we consider that the method proposed in this study realizes the application of smallsample uncertainty analysis in reliability analysis, and could provide a feasible way to solve the similar problems in engineering with multidimensional and small-sample parameters.     

Multi-parameter optimization of machining impeller surface based on the on-machine measuring technique

Selecting the optimal machining parameters for impeller surface is a challenging task in the automatic manufacturing industry, due to its free-form surface and deep-crooked flow channel. Existing experimental methods require lots of machining experiments and off-line tests, which may lead to high machining cost and low efficiency. This paper proposes a novel method of machining parameters optimization for an impeller based on the on-machine measuring technique. The absolute average error and standard deviation of the measured points are used to define the grey relational grade for reconstructing the objective function, and the complex problem of multi-objective optimization is simplified into a problem of single-objective optimization. Then, by comparing the values of the defined grey relational grade in a designed orthogonal experiment, the optimal combination of the machining parameters is obtained. The experiment-solving process of the objective function corresponds to the minimization of the used errors, which is advantageous to reducing the machining error. The proposed method is efficient and low-cost, since it does not require re-clamping the workpiece for off-line tests. Its effectiveness is verified by an on-machine inspection experiment of the impeller blade.     

Analytical and numerical approaches of a solar array thermal analysis in a low-earth orbit satellite

This paper researches the thermal analysis of a fixed-type solar array in a low-earth orbit satellite through both an analytical method with a simplified thermal model and a numerical method with a detailed thermal model.     

高温不锈钢的磨削温度测量与烧伤现象分析

针对高温不锈钢1Cr11Ni2W2MoV磨削过程中磨削区内部瞬时温度、磨削表面平均温度的测量方法以及工件表面平均温度与烧伤程度之间的关系进行了研究,分析了工件表面烧伤程度对材料金相组织的影响.通过研究得到了陶瓷结合剂CBN砂轮磨削1Cr11Ni2W2MoV时磨削区内部瞬时温度,证明工件表面的烧伤最直接因素是磨削表面的平均温度,在不同的磨削参数下,表面平均温度超过540℃就形成黄色的微烧伤,随着温度的升高,烧伤程度不断加重.同时,表面烧伤会使马氏体晶格变成细小的退火微晶变质层,烧伤越严重,微晶变质层的厚度越大.