压电式压力传感器的动态校准

通常对压电式压力传感器进行静态校准是有困难的。主要原因是放大器输入级的时间常数不够大,产生的电荷易被漏掉,因而输出电压不能保持在常值上。本文叙述了一种压力校准装置,用它可对压电式压力传感器的灵敏度进行绝对法和比较法校准。该装置能在5～10ms的时间内爆发出1高达1MPa的阶跃脉冲压力。压力传感器及其测量系统对此阶跃脉冲压力的响应,用微处理机处理,可自动给出压力灵敏度、响应曲线及其有关参数。校准精度约为1％。     

地球同步组合卫星

1945年10月,英国人阿瑟·克拉克在《无线电世界》杂志上发表了《地球外的中继站》一文,设想以三个间隔120度角的人造卫星,等间距放在赤道上空大约35800km的地球同步轨道上,就可以实现全球通信。1965年,克拉克的设想变成了现实。     

无人机传感器 市场前景广阔

Frost＆Sullivan公司最近发布了一份关于无人机传感器载荷市场的预测报告。该报告认为，由于市场对无人机的需求持续走高，故其机载传感器市场也将在未来获得极大发展，光电（EO）、红外（IR）和具有地面动目标指示能力的合成孔径雷达（SAR／GMTI）三大类传感器将成为所有新型无人机平台的标准装备选项。在最近的实际使用中，这些无人机传感器确实增强了部队的态势感知和交战能力。     

传感器安装对爆炸冲击测试结果影响的试验研究

为了找到爆炸冲击测试结果精确度的影响因素,利用轻气炮冲击试验装置作为冲击源,设计了专用对比工装,模拟安装过程中的实际操作因素的影响程度。以压阻式传感器为研究对象,以激光多普勒测振仪校准结果为基准,对比耦合剂种类、连接螺栓规格、表面粗糙度、安装力矩以及传感器安装数量等因素对测试结果的影响。结果表明前4种因素对冲击测试的影响较小,均在3 dB的容差范围以内;而传感器安装数量和与被测对象的连接方式对冲击测试结果影响较大。     

基于一致关联数最大化的航迹关联算法

航迹关联(TTTA)是多传感器数据融合系统的核心模块之一,是系统误差估计和航迹融合的前提和基础。传感器存在的固有系统误差使得目标位置状态估计与真值发生偏离,容易诱发TTTA错误。传统的基于全局最小距离准则的TTTA算法,需要获得较高精度的系统误差估计,来对航迹数据进行误差补偿。针对传感器具有系统误差环境下的TTTA问题,在对TTTA进行间接评估的基础上,定义了一致关联数的概念,提出了一致关联数最大化的TTTA准则,并在稳健交替迭代的框架下完成算法设计。与距离函数不同,一致关联数是一个离散量,放松了对系统误差估计精度的要求。最后,仿真实验验证了所提算法的有效性。     

一类空间对称6R机构的运动学研究及组合应用

可展开平板机构已广泛应用于平板天线、太阳翼等航天机构产品。为提高可展开平板机构的刚度和展收比,将空间对称6R机构应用于可展开平板机构设计。首先,根据约束条件,计算后给出了一种空间3R运动链的几何参数关系;然后,结合螺旋理论,分析了该3R运动链的约束螺旋系;进而根据对称性,研究了空间对称6R机构的自由度、奇异性等运动特征;在此基础上,提出了一种特殊的空间对称6R转动机构;最后,研究了空间对称6R机构的组合方法,设计出一种新型单自由度可展开平板组合机构,并对其进行了运动学仿真验证。该可展机构具有二维方向的展开收拢能力,为可展开平板机构的创新设计提供了有益参考。     

涡轮冲压组合发动机技术发展

涡轮冲压组合发动机是实现高超声速飞行的关键动力装置,其中高速涡轮发动机是技术研究重点。虽然由于技术难度过高,所需经费巨大,但是涡轮冲压组合发动机的研究仍然取得了一定的研究成果。     

A strategic flight conflict avoidance approach based on a memetic algorithm

Conflict avoidance （CA） plays a crucial role in guaranteeing the airspace safety. The cur- rent approaches, mostly focusing on a short-term situation which eliminates conflicts via local adjust- ment, cannot provide a global solution. Recently, long-term conflict avoidance approaches, which are proposed to provide solutions via strategically planning traffic flow from a global view, have attracted more attentions. With consideration of the situation in China, there are thousands of flights per day and the air route network is large and complex, which makes the long-term problem to be a large-scale combinatorial optimization problem with complex constraints. To minimize the risk of premature convergence being faced by current approaches and obtain higher quality solutions, in this work, we present an effective strategic framework based on a memetic algorithm （MA）, which can markedly improve search capability via a combination of population-based global search and local improve- ments made by individuals. In addition, a specially designed local search operator and an adaptive local search frequency strategy are proposed to improve the solution quality. Furthermore, a fast genetic algorithm （GA） is presented as the global optimization method. Empirical studies using real traffic data of the Chinese air route network and daily flight plans show that our approach outper- formed the existing approaches including the GA .based approach and the cooperative coevolution based approach as well as some well-known memetic algorithm based approaches.     

A salient edges detection algorithm of multi-sensor images and its rapid calculation based on PFCM kernel clustering

Multi-sensor image matching based on salient edges has broad prospect in applications, but it is difficult to extract salient edges of real multi-sensor images with noises fast and accurately by using common algorithms. According to the analysis of the features of salient edges, a novel salient edges detection algorithm and its rapid calculation are proposed based on possibility fuzzy C-means （PFCM） kernel clustering using two-dimensional vectors composed of the values of gray and texture. PFCM clustering can overcome the shortcomings that fuzzy C-means （FCM） cluster- ing is sensitive to noises and possibility C-means （PCM） clustering tends to find identical clusters. On this basis, a method is proposed to improve real-time performance by compressing data sets based on the idea of data reduction in the field of mathematical analysis. In addition, the idea that kernel-space is linearly separable is used to enhance robustness further. Experimental results show that this method extracts salient edges for real multi-sensor images with noises more accurately than the algorithm based on force fields and the FCM algorithm; and the proposed method is on average about 56 times faster than the PFCM algorithm in real time and has better robustness.     

Investigations into sensing characteristics of circular thin-plate electrostatic sensors for gas path monitoring

Circular thin-plate electrostatic sensors are promising in gas path monitoring due to their advantages of non-intrusiveness and easy installation. The spatial sensitivity and filtering effect are two important performance parameters. In this paper, an analytically mathematical model of induced charge on a circular thin-plate electrode is first derived. Then the spatial sensitivity and filtering effect of the circular electrostatic sensor are investigated by numerical calculations. Finally,experimental studies are performed to testify the theoretical results. Both theoretical and experimental results demonstrate that circular thin-plate electrostatic sensors act as a low-pass filter in the spatial frequency domain, and both the spatial filtering effect and the temporal frequency response characteristics depend strongly on the spatial position and velocity of the charged particle. These conclusions can provide guidelines for the optimal design of circular thin-plate electrostatic sensors.