基于双循环的涡轮叶冠多学科设计优化

针对经典的多学科设计可行方法(MDF)的低效率问题,开展了利用可变复杂度建模方法改进MDF策略的研究.以涡轮叶冠为对象,综合考虑优化精度和优化效率,利用响应面方法近似高精度分析,简化计算难度,提高优化效率;合理引入可变复杂度建模方法,通过双循环结构优化策略周期性地调用高精度分析更新响应面方程来保证优化精度.基于双循环的涡轮叶冠多学科优化设计(MDO)表明,优化设计目标降低了1.4%,明显好于经典MDF策略(0.97%),整个优化策略共耗时2h39min,仅是经典MDF的优化时间的1/3.     

曲面零件五坐标扫描检测路径产生方法研究

针对曲面零件对五坐标扫描检测的需求,在对REVO五坐标旋转扫描测头的技术特征进行分析的基础上,提出了适用于五坐标扫描检测路径规划的球面法,通过测尖运动球形包络面与被测工件曲面的相交线来确定检测路径,测量主要由测尖扫描完成,减少测量机的三轴移动,实现高速坐标扫描测量。     

基于动态面法的导弹制导控制一体化设计方法研究

为避免传统导弹制导和控制系统单独设计存在的缺陷,将两个系统综合考虑,提出一种制导控制一体化设计方法。首先推导出俯仰通道的制导控制一体化数学模型,并化为级联形式;然后引入动态面方法并结合非线性干扰观测器技术,提出了一种基于非线性干扰观测器的积分动态面一体化制导控制系统设计方法,在每一个子系统设计时引入误差的积分项以消除稳态误差,提高了子系统的跟踪精度;采用Lyapunov函数对系统稳定性进行了分析;最后通过仿真验证了所提出的一体化控制算法的有效性。     

弱模型依赖通用智能姿态控制技术

超高速跨域飞行、敏捷机动等是新一代飞行器发展方向,而长时高速飞行产生的气动外形变化带来的气动参数大范围改变等问题,都对控制系统设计提出了更高的要求。为提高飞行器对模型不确定性的适应能力及控制方法对不同外形、复合执行机构的通用性,深入研究了弱模型依赖的通用智能姿态控制技术,分层次地开展了基于深度学习(DL)的自适应姿态控制、基于深度确定性策略梯度算法(DDPG)的通用姿态控制、弱模型依赖的多维复合控制等技术研究,显著提高了控制系统的鲁棒性和通用性,对人工智能技术在飞行器姿态控制中的应用具有一定的指导意义。     

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.