基于形貌优化法的无轴承开关磁阻电机减振降噪

脉振的径向电磁力作为激励源作用于12/8极单绕组宽转子齿无轴承开关磁阻电机（Bearingless switched reluctance motor with wider rotor teeth,BSRMWR）的定子齿面并传送至定子轭部及机壳,会引发较大的振动噪声,阻碍其推广应用。针对这一问题,本文从本体结构的角度入手对电机壳体进行优化改进。采用三维多物理场有限元模型,建立了BSRMWR电磁-结构-振动-声场耦合模型。通过对BSRMWR电磁场进行瞬态分析,得到径向电磁力。将模态应变能方法应用于BSRMWR的壳体得到电机外壳结构有较大的应变能,说明电机壳体结构的薄弱。基于此,通过形貌优化的方法对电机的壳体结构进行优化。结果表明,采用形貌优化后机壳结构的BSRMWR,其振动和噪声均有显著改善。     

基于非连续算子广义变分不等式强解的存在性

在算子不连续的情况下,利用FKKM定理和Weierstrass定理及标量化方法得到了广义向量变分不等式的强解存在性定理.     

细长杆降低超声速客机气动噪声的数值分析

在超声速客机机头加装适当的细长杆可以降低飞行噪声。本文借助基于AUSM+格式的准三维数值模拟手段对7组13种细长杆方案做了分析比较,总结出了近场气体参数与远场气体参数之间的关系的规律。文章还从气体动力学理论和激波理论出发,对数值模拟结果作了解释,并揭示了细长杆降噪效果与细长杆外形的内在联系,以及近场、远场两者关系的经验公式。文章从各种方案中选取了降噪效果较好的细长杆方案做三维流场分析,并通过流固耦合计算对其结构强度做了校核,验证了方案的可行性。     

基于循环平稳性的噪声调频干扰高分辨测向方法

根据噪声调频信号循环平稳特性分析,提出了基于阵列接收信号循环均值-空域处理的波达方向(DOA)估计算法。仿真结果表明:该算法的角度估计性能明显高于比幅比相单脉冲测角法,且在高信噪比环境中,该法的估计性能更好、运算量较小。     

风扇进口噪声预测模型的改进

针对Heidmann模型对风扇进口低频噪声(1k Hz)预测结果偏低的情况,通过引入风扇叶尖弦长雷诺数和相关几何参数改进了Heidmann模型中风扇进口宽频噪声的频谱修正函数,确定了其中频谱修正系数为0.085。对比改进模型和Heidmann模型的风扇进口噪声预测结果发现:在亚声速工况下,改进的模型很好地改善了风扇进口低频噪声的预测结果,改进幅值可以达到约45d B;而在超声速工况下,由于风扇进口产生的组合单音噪声成为风扇进口噪声的主要组成部分,除了在小于100Hz的频域内,改进的模型与Heidmann模型的预测结果差别不大。     

一种基于机动辨识预测的空空导弹导引律

现有的空空导弹导引头在有噪声和干扰的环境下获得目标精确信息存在时间延迟,且新一代目标的机动能力更强,不对导弹加以补偿会造成较大脱靶量,所以需对目标状态有效预测。针对新一代目标规避空空导弹常用的大机动模式,为满足新一代空空导弹发展需求,设计了一种新型复合导引律。从目标自身出发,研究高机动目标规避导弹采用的典型机动形式,对机动轨迹进行离线建模,构建具有扩展能力的目标机动模型库。设计自适应滤波器对测量噪声进行降噪。同时,利用模型库设计了机动辨识预测器,对目标实际机动进行在线辨识。基于在线辨识的结果对目标机动进行预测,并对时间延迟进行补偿和修正,实现对高机动目标的精确打击。仿真结果表明:该方法对不同类型的机动目标均有较高的预测精度和命中精度。     

Noise analysis of continuous GPS coordinate time series for CMONOC

The Crustal Movement Observation Network of China (CMONOC) is one of the major scientific infrastructures, mainly using Global Positioning System (GPS) measurements, to monitor crustal deformation in the Chinese mainland. In this paper, decade-long coordinate time series of 26 continuous GPS sites of CMONOC are analyzed for their noise content using maximum likelihood estimation (MLE). We study the noise properties of continuous GPS time series of CMONOC for the unfiltered, filtered solutions and also the common mode signals in terms of power law plus white noise model. In the spatial filtering, we remove for every time series a common mode error that was estimated from a modified stacking of position residuals from other sites within ∼1000 km of the selected site. We find that the common mode signal in our network has a combination of spatially correlated flicker noise and a common white noise with large spatial extent. We demonstrate that for the unfiltered solutions of CMONOC continuous GPS sites the main colored noise is a flicker process, with a mean spectral index of ∼1. For the filtered solutions, the main colored noise is a general power law process, indicating that a major number of the filtered regional solutions have a combination of noise sources or local effects. The velocity uncertainties from CMONOC continuous GPS coordinate time series may be underestimated by factors of 8–16 if a pure white noise model is assumed. In addition, using a white plus flicker noise model, the median values of velocity errors for the unfiltered solutions are 0.16 (north), 0.17 (east) and 0.58 (vertical) mm/yr, and the median values for the filtered solutions are 0.09 (north), 0.10 (east) and 0.40 (vertical) mm/yr.     

CCD信号采样位置选取方法的研究

针对CCD输出信号中的复位噪声,文章介绍了处理复位噪声较为常用的方法--相关双采样技术,并对相关双采样技术中采样位置选取的方法进行分析和研究,最后进行了实验验证.结果表明:用文中方法选取的采样位置进行相关双采样,可以较好的减小CCD输出信号中复位噪声的影响,提高信噪比.     

空客A320飞机驾驶舱异响故障的排除

针对航线维护中一起不寻常的驾驶舱啸叫故障,参考空客公司的建议,结合实际航线维护经验,总结出系列驾驶舱异常噪声故障的可能来源,对类似故障的排除和隔离具有一定的参考意义。     

An artificial neural network approach for aerodynamic performance retention in airframe noise reduction design of a 3D swept wing model

With the progress of high-bypass turbofan and the innovation of silencing nacelle in engine noise reduction, airframe noise has now become another important sound source besides the engine noise. Thus, reducing airframe noise makes a great contribution to the overall noise reduction of a civil aircraft. However, reducing airframe noise often leads to aerodynamic perfor-mance loss in the meantime. In this case, an approach based on artificial neural network is intro-duced. An established database serves as a basis and the training sample of a back propagation (BP) artificial neural network, which uses confidence coefficient reasoning method for optimization later on. Then the most satisfactory configuration is selected for validating computations through the trained BP network. On the basis of the artificial neural network approach, an optimization pro-cess of slat cove filler (SCF) for high lift devices (HLD) on the Trap Wing is presented. Aerody-namic performance of both the baseline and optimized configurations is investigated through unsteady detached eddy simulations (DES), and a hybrid method, which combines unsteady DES method with acoustic analogy theory, is employed to validate the noise reduction effect. The numerical results indicate not merely a significant airframe noise reduction effect but also excel-lent aerodynamic performance retention simultaneously.