应用虚拟样机技术优化设计卡钳

分析了传统设计方法的弊端,介绍虚拟样机技术这一全新的设计方法.以应用动力学仿真软件ADAMS建造卡钳虚拟样机优化设计的实例,说明虚拟样机技术可以缩短开发周期、降低成本,提高设计质量和可靠性.     

基于数值模拟的拔伸成形工艺分析与优化

变薄拔伸是厚壁深筒件生产的关键工序,成形难度大.针对现行的拔伸成形工艺,为改善成形稳定性、提高成形质量、延长模具寿命,通过采用刚粘塑性有限元法,根据不同参数和条件,在计算机上对拔伸工艺进行数值模拟分析,分别讨论了拔伸模圈道数、变形量分配、模圈间距及入模角等因素对拔伸成形过程的影响,进而提出了"多模短距长拔"、变形量依次递减和较小入模角等优化措施.这样既减少了大量现场试验,又达到了工艺优化的目的.     

IIR数字滤波器联立优化CAD

文中介绍了多目标联立最佳逼近CAD方法,对各种设计方法的性能作了分析比较,提出了改善途径。程序在IBM-PC/XT微机上运行通过,文中给出了应用线性相位IIR数字滤波器线性规划逼近法设计的低通实例。     

基于约束满足的多目标对地观测卫星成像调度

EOS(对地观测卫星)成像调度需要根据用户提出的成像任务需求确定卫星成像序列,是一个复杂的组合优化问题。考虑到成像侧视约束条件,建立EOS成像调度的多目标有向无环约束图模型。在此模型的基础上提出了基于SPEA2(strength pareto evolutionary algorithm 2)的多目标成像调度算法,采用约束控制技术设计遗传算子处理成像约束。经过三个实际的多目标成像调度问题测试,表明该算法可以有效地解决EOS成像调度问题。     

超燃冲压发动机燃烧室构型优化的试验研究

在直连式超燃冲压发动机试验系统上,通过调节超燃冲压发动机燃烧室壁面扩张角和燃料喷注位置,对燃烧室构型优化进行了试验研究。为了提高试验效率,燃烧室形面调节采用正交试验设计方法进行组织,每个形面进行5种喷注位置的试验,每次试验通过文氏管调节3个当量比的燃料流量。利用试验数据构造燃烧室性能关于构型参数的响应面模型,可用于燃烧室构型优化。通过两次渐进优化获得了性能更优的燃烧室构型,并根据试验数据分析了各构型参数对燃烧室性能的影响,结果表明:优化构型燃烧室的推力增益比基准构型增大了10.4%;燃烧室性能受各构型参数的强烈耦合影响。     

A novel noise reduction technique for underwater acoustic signals based on complete ensemble empirical mode decomposition with adaptive noise,minimum mean square variance criterion and least mean square adaptive filter

Underwater acoustic signal processing is one of the research hotspots in underwater acoustics. Noise reduction of underwater acoustic signals is the key to underwater acoustic signal processing. Owing to the complexity of marine environment and the particularity of underwater acoustic channel, noise reduction of underwater acoustic signals has always been a difficult challenge in the field of underwater acoustic signal processing. In order to solve the dilemma, we proposed a novel noise reduction technique for underwater acoustic signals based on complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN), minimum mean square variance criterion (MMSVC) and least mean square adaptive filter (LMSAF). This noise reduction technique, named CEEMDAN-MMSVC-LMSAF, has three main advantages: (i) as an improved algorithm of empirical mode decomposition (EMD) and ensemble EMD (EEMD), CEEMDAN can better suppress mode mixing, and can avoid selecting the number of decomposition in variational mode decomposition (VMD); (ii) MMSVC can identify noisy intrinsic mode function (IMF), and can avoid selecting thresholds of different permutation entropies; (iii) for noise reduction of noisy IMFs, LMSAF overcomes the selection of decomposition number and basis function for wavelet noise reduction. Firstly, CEEMDAN decomposes the original signal into IMFs, which can be divided into noisy IMFs and real IMFs. Then, MMSVC and LMSAF are used to detect identify noisy IMFs and remove noise components from noisy IMFs. Finally, both denoised noisy IMFs and real IMFs are reconstructed and the final denoised signal is obtained. Compared with other noise reduction techniques, the validity of CEEMDAN-MMSVC-LMSAF can be proved by the analysis of simulation signals and real underwater acoustic signals, which has the better noise reduction effect and has practical application value. CEEMDAN-MMSVC-LMSAF also provides a reliable basis for the detection, feature extraction, classification and recognition of underwater acoustic signals.     

A guarantee rate optimization model for wastewater treatment system design under uncertainty

We consider a design problem for wastewater treatment systems that considers uncertainty in pollutant concentration levels at water sources. The goal is to optimize the selection of treatment technologies and pipeline connections, so that treated wastewater can achieve specified effluents discharge limits as well as possible. We propose a new two-stage model to optimize a set of guarantee levels, that is, the maximum concentration level of source pollutants for which treated wastewater can be compliant with discharge limits. In the first stage, treatment technologies and pipeline connections are selected. In the second stage, when pollutant concentration levels are revealed, wastewater distribution and mixing are determined. A key attractiveness of the proposed guarantee rate optimization model is that it can be simplified into a single-stage mixed-integer linear program. In our numerical experiments based on real-world pollutants data, the guarantee rate model demonstrates its advantages in terms of computational efficiency, scalability and solution quality, compared with the standard probability maximization model. Finally, the methodology proposed in this paper can also be applied to other two-stage problems under uncertainty with similar uncertainty characteristics.     

基于不完全测量数据的飞行器轨迹参数估计

提出基于稀疏优化的轨迹参数估计新方法,通过降低参数空间的维数改善模型的病态性。利用B样条函数实现轨迹参数的稀疏表示,根据轨迹参数与测量数据的关系建立估计轨迹参数的稀疏表示寻优模型,采用高斯牛顿法获得模型的解。寻优模型中待估参数的数量取决于样条节点数,利用样条函数的高阶导数在节点处的不连续性建立了选取样条节点的稀疏优化模型,采用凸优化方法求解该模型,实现样条节点数的最小化。仿真结果表明,稀疏优化方法能够大幅度提高不完全测量段落轨迹参数的估计精度。     

多重优化的分布式无线覆盖探测算法

为满足无线通信网络信号覆盖有效性的实时实地可重复探测的需求,提出一种基于传感器网络的分布式无线覆盖探测算法。通过随机部署于目标区域内的无线传感器节点对无线通信网接收信号强度进行感知和预处理;利用变异函数构造新的BP神经网络目标函数,通过改进粒子群算法优化其初始权值和阈值;利用训练好的网络模型对存在探测盲区的目标区域进行插值估计,并联合传感器节点采集到的数据生成无线通信网络等信号强度线。仿真结果表明,所提算法比其他经典算法具有更高的精度,可有效探测目标区域无线通信网络的信号覆盖情况。     

基于粒子群算法的宽带真延时平面阵列方向图综合

针对大阵元间距平面阵列方向图综合问题,提出基于粒子群算法的宽带真延时平面阵列方向图综合方法。该方法根据真延时条件下阵列方向图主瓣和栅瓣指向的特点,采用宽带真延时抑制阵列方向图的栅瓣;利用粒子群优化算法优化阵列结构,得到具有较高主副瓣比的平面阵列方向图。通过对8×8的矩形平面阵进行仿真,验证了所提方法的有效性,在此基础上,还仿真研究了该方法对栅瓣的抑制性能与信号带宽之间的关系。