基于跨层信道感知的SPMA 协议自适应阈值算法

基于统计优先级的多址接入协议（SPMA, Statistical Priority-based Multiple Access protocol）应用于机     

Derivation and validation of a similarity law for free-flight wind tunnel tests of parallel stage separation

Aiming at the safety problem of the stage separation of parallel reusable high-speed air vehicles, this paper studies the unsteady test method and focuses on deriving a similarity law of parallel stage separation free-flight wind tunnel tests. The new similarity law considers the influences of aerodynamic force and gravity on the motions of the two stages, as well as the influence of aerodynamic interference between the two stages on each other’s motion. From the perspective of multi-angle physical equations, the conditions to ensure that the two-stage separation trajectory of a wind tunnel test is similar to that of a real air vehicle are derived innovatively, so as to ensure the authenticity and credibility of wind tunnel test results. The similarity law is verified by an HIFiRE-5 air vehicle, and the separation trajectories of wind tunnel tests and the real air vehicle are obtained by numerical simulation. The research shows that the similarity law derived in this paper can ensure that wind tunnel free-flight tests have the ability to predict the two-stage separation characteristics of real parallel vehicles. By analyzing the separation trajectory curve of the typical state, it is found that the new method can ensure that the trajectory error of a wind tunnel test does not exceed 1%, which indicates that this method is credible. The establishment of the new method lays the foundation for subsequent wind tunnel tests and provides support for research on the safety of the stage separation of parallel reusable air vehicles.     

基于自适应遗传算法的DGPS整周模糊度快速解算

 鉴于遗传算法(GA)所具有的全局搜索特性,也为了更快速准确地解算差分全球定位系统(DGPS)整周模糊度,将自适应遗传算法(AGA)引入DGPS整周模糊度的搜索中。首先根据全球定位系统(GPS)载波相位双差方程求解出双差整周模糊度的浮点解,并以基线长度作为约束条件确定整周模糊度的搜索范围;然后利用白化滤波的方法对整周模糊度进行降相关处理,降低整周模糊度各分量之间的相关性;最后将自适应遗传算法应用在整周模糊度的解算过程中,搜索整周模糊度的最优解。仿真计算结果表明,与LAMBDA算法和简单遗传算法相比,自适应遗传算法能够快速地求解整周模糊度,也具有较好的可靠性和鲁棒性。     

基于CEEMDAN降噪与双谱分析的滚动轴承故障诊断

滚动轴承早期故障信号中的噪声成分会影响到故障特征的提取。为了提高含噪故障信号中滚动轴承早期故障特征提取的准确性,将基于自适应噪声的完备经验模态分解（CEEMDAN）用于滚动轴承振动信号的降噪中,并对降噪后的轴承故障信号进行双谱分析。结果表明：CEEMDAN可有效去除轴承振动信号中的低频噪声干扰,经CEEMDAN降噪后的不同轴承故障信号的双谱全局图存在明显差异,根据这些差异可在宏观上对不同轴承故障加以区分;通过经CEEMDAN降噪后的不同轴承故障信号的双谱细节图可以正确提取不同轴承故障的特征频率,从而实现对各轴承故障的有效诊断。CEEMDAN降噪结合双谱分析可为滚动轴承故障诊断提供一种新的有效方法。     

基于终端滑模的无人机编队协同控制

文章研究了具有输入受限及外部干扰的无人机编队有限时间协同控制问题。首先,引入抗饱和辅助系统来解决执行器的饱和问题,利用自适应方法对扰动上界进行估计和补偿;然后,设计新型全局快速终端滑模的控制器,使得编队内各无人机在有限时间内收敛到指定的编队位置,并通过李雅普诺夫稳定性分析方法,证明控制方法的有效性;最后,对提出的控制方法进行数字仿真,验证了实际可行性。     

叶片振动可靠性评估方法研究

提出一种用于发动机叶片振动可靠性评估方法,该方法基于叶片共振转速图（Ｃａｍｐｂｅｌ）,引入概率故障树ＰＦＴＡ（ＰｒｏｂａｂｉｌｉｔｙＦａｕｌｔＴｒｅｅＡｎａｌｙｓｉｓ）概念,改善了传统评估方法。其目的是为发展叶片共振识别和可靠性评估的有效方法。在Ｃａｍｐｂｅｌ图上,叶片共振系统定义由工作转速点和附近的多个共振点组成。利用ＰＦＴＡ分析该系统能获得更多的叶片振动信息。该方法发展了常规的叶片振动可靠性设计方法,为叶片设计和叶片振动疲劳排故中改善叶片振动特性提供有益的工程评估方法。     

Variable structure multiple model fixed-interval smoothing

This paper focuses on fixed-interval smoothing for stochastic hybrid systems. When the truth-mode mismatch is encountered, existing smoothing methods based on fixed structure of model-set have significant performance degradation and are inapplicable. We develop a fixed-interval smoothing method based on forward- and backward-filtering in the Variable Structure Multiple Model (VSMM) framework in this paper. We propose to use the Simplified Equivalent model Interacting Multiple Model (SEIMM) in the forward and the backward filters to handle the difficulty of different mode-sets used in both filters, and design a re-filtering procedure in the model-switching stage to enhance the estimation performance. To improve the computational efficiency, we make the basic model-set adaptive by the Likely-Model Set (LMS) algorithm. It turns out that the smoothing performance is further improved by the LMS due to less competition among models. Simulation results are provided to demonstrate the better performance and the computational efficiency of our proposed smoothing algorithms.     

Geometry and size optimization of stiffener layout for three-dimensional box structures with maximization of natural frequencies

Based on the growth mechanism of natural biological branching systems and inspiration from the morphology of plant root tips, a bionic design method called Improved Adaptive Growth Method (IAGM) has been proposed in the authors’ previous research and successfully applied to the reinforcement optimization of three-dimensional box structures with respect to natural frequencies. However, as a kind of ground structure methods, the final layout patterns of stiffeners obtained by using the IAGM are highly subjected to their ground structures, which restricts the optimization effect and freedom to further improve the dynamic performance of structures. To solve this problem, a novel post-processing geometry and size optimization approach is proposed in this article. This method takes the former layout optimization result as start, and iteratively finds the optimal layout angles, locations, and lengths of stiffeners with a few design variables by optimizing the positions of some specific node lines called active node lines. At the same time, thicknesses of stiffeners are also optimized to further improve natural frequencies of three-dimensional box structures. Using this method, stiffeners can be successfully separated from their ground structures and further effectively improve natural frequencies of three-dimensional box structures with less material consumption. Typical numerical examples are illustrated to validate the effectiveness and advantages of the suggested method.     

红外光学式二氧化碳分压传感器

介绍一种红外光学式二氧化碳分压传感器，该传感器基于朗伯－比尔定律，采用光源稳流，单片机温度偿及选用高性能红外探测器等技术，能够对二氧化碳气体进行有效准确地测量和分析，且结构简单，体积小，重量轻，功耗低，响应速度快，可靠性高，具有广阔的应用前景。     

大攻角飞行时机翼摇摆问题的神经网络控制方案

提出了一种基于神经网络的自适应控制方案,这种方案能够在对被控对象几乎没有先验知识的情况下对其实施有效的控制,对一个具有不稳定机翼摇摆问题的薄三角翼飞机模型的仿真证实了本方法的有效性。