飞机智慧座舱发展技术研究

未来飞机座舱智慧化转型是必然趋势,研究飞机智慧座舱发展技术能够为未来飞机智慧座舱的设计提供参考支撑。本文探讨了智能与智慧的区别,提出了飞机智慧座舱的概念与设计内涵,总结出深度感知与沉浸式交互、类人的认知及开放性与个性化定制服务的智慧座舱功能设计要素;梳理了发展飞机智慧座舱亟需解决的五项关键技术：多维度深度信息感知与融合技术、先进信息显示技术、沉浸式自然交互技术、智能态势认知技术、多智能体自主适应技术。通过关键技术的分析对未来飞机智慧座舱的发展提出了新的思考。     

Monocular Vision-based Two-stage Iterative Algorithm for Relative Position and Attitude Estimation of Docking Spacecraft

Visual sensors are used to measure the relative state of the chaser spacecraft to the target spacecraft during close range rendezvous phases. This article proposes a two-stage iterative algorithm based on an inverse projection ray approach to address the relative position and attitude estimation by using feature points and monocular vision. It consists of two stages: absolute orientation and depth recovery. In the first stage, Umeyama's algorithm is used to fit the three-dimensional (3D) model set and estimate the 3D point set while in the second stage, the depths of the observed feature points are estimated. This procedure is repeated until the result converges. Moreover, the effectiveness and convergence of the proposed algorithm are verified through theoretical analysis and mathematical simulation.     

基于人工神经网络的道路表面降雨水深预测

建立了基于人工神经网络的道路表面水膜厚度预测模型,通过试验数据的训练确定权重和阈值,经过检验样本的检验,能够很好地预测道路表面的水膜厚度。结果表明,本文建立的人工神经网络模型用于道路表面水膜厚度预估可行。     

自适应融合 RGB图像特征的稀疏深度修复

深度修复的目的是从稀疏深度图像中恢复出稠密的深度图像。现有方法通常是以稀疏深度图像及其对应的 RGB图像为输入,通过 1个卷积神经网络恢复出密集深度图像。然而,普通的卷积层在处理稀疏且不规则的深度信息时有较大的局限性,同时,RGB图像特征和深度图像特征属于不同的模态。针对这些问题,文章提出了自适应稀疏不变模块,根据输入像素的有效性来处理稀疏深度,并提出了结合注意力机制的多尺度特征融合模块,在关注有效特征的同时,抑制不必要的特征,进一步提高深度修复性能。文章在 NYUv2数据集上进行了一系列实验,实验结果表明了所提出算法和模块的有效性。     

基于多特征融合的航天器锂电池健康评估技术

传统的航天器蓄电池可靠性试验按照最大放电深度进行定额充放电，所构建的失效模型用于支撑航天器总体可靠性设计，不能用于在轨锂离子蓄电池健康评估任务；航天器在蓄电池遥测的采样率、精度、样本量方面无法与民用领域相比，基于高采样、大样本的民用蓄电池健康估计方法也不适用于在轨锂离子蓄电池健康评估。针对该问题，从在轨航天器蓄电池数据特性出发，挖掘在轨状态下所能提取的退化特征，并采用多特征综合评价方法，设计了一种基于多特征融合的在轨锂离子蓄电池健康评估方法，实现了在轨蓄电池放电内阻、同放电深度下的终端电压、恒压充电时间3项退化特征融合的健康量化评估，应用于某型号卫星的在轨监测与健康评估，具有良好的工程实用性，可作为国内航天器健康评估技术的参考。     

发动机叶片气相渗铝工艺研究

为提高发动机叶片抗高温氧化和抗燃气腐蚀的能力,选用发动机叶片气相渗铝工艺,通过模拟生产的工艺试验,以试验数据及现象为依据,客观分析了渗铝的加热温度、保温时间及渗铝剂的用量等因素对渗铝层深度的影响,从而确定某型发动机叶片气相渗铝时的热处理参数。     

Langley method applied in study of aerosol optical depth in the Brazilian semiarid region using 500, 670 and 870 nm bands for sun photometer calibration

Due to the high costs of commercial monitoring instruments, a portable sun photometer was developed at INPE/CRN laboratories, operating in four bands, with two bands in the visible spectrum and two in near infrared. The instrument calibration process is performed by applying the classical Langley method. Application of the Langley’s methodology requires a site with high optical stability during the measurements, which is usually found in high altitudes. However, far from being an ideal site, Harrison et al. (1994) report success with applying the Langley method to some data for a site in Boulder, Colorado. Recently, Liu et al. (2011) show that low elevation sites, far away from urban and industrial centers can provide a stable optical depth, similar to high altitudes. In this study we investigated the feasibility of applying the methodology in the semiarid region of northeastern Brazil, far away from pollution areas with low altitudes, for sun photometer calibration. We investigated optical depth stability using two periods of measurements in the year during dry season in austral summer. The first one was in December when the native vegetation naturally dries, losing all its leaves and the second one was in September in the middle of the dry season when the vegetation is still with leaves. The data were distributed during four days in December 2012 and four days in September 2013 totaling eleven half days of collections between mornings and afternoons and by means of fitted line to the data V₀ values were found. Despite the high correlation between the collected data and the fitted line, the study showed a variation between the values of V₀ greater than allowed for sun photometer calibration. The lowest V₀ variation reached in this experiment with values lower than 3% for the bands 500, 670 and 870 nm are displayed in tables. The results indicate that the site needs to be better characterized with studies in more favorable periods, soon after the rainy season.     

Accuracy analysis of GNSS-IR snow depth inversion algorithms

In recent years, with the continuous development of Global Navigation Satellite System (GNSS), it has been applied not only to navigation and positioning, but also to Earth surface environment monitoring. At present, when performing GNSS-IR (GNSS Interferometric Reflectometry) snow depth inversion, Lomb-Scargle Periodogram (LSP) spectrum analysis is mainly used to calculate the vertical height from the antenna phase center to the reflection surface. However, it has the problem of low identification of power spectrum analysis, which may lead to frequency leakage. Therefore, Fast Fourier Transform (FFT) spectrum analysis and Nonlinear Least Square Fitting (NLSF) are introduced to calculate the vertical height in this paper. The GNSS-IR snow depth inversion experiment is carried out by using the observation data of P351 station in PBO (Plate Boundary Observatory) network of the United States from 2013 to 2016. Three algorithms are used to invert the snow depth and compared with the actual snow depth provided by the station 490 in the SNOTEL network. The observations data of L1 and L2 bands are respectively used to find the optimal combination between different algorithms further to improve the accuracy of GNSS-IR snow depth inversion. For L1 band, different snow depths correspond to different optimal algorithms. When the snow depth is less than 0.8 m, the inversion accuracy of NLSF algorithm is the highest. When the snow depth is greater than 0.8 m, the inversion accuracy of FFT algorithm is higher. Therefore, according to the different snow depth, a combined algorithm of NLSF + FFT is proposed for GNSS-IR snow depth inversion. Compared with the traditional LSP algorithm, the inversion accuracy of the combined algorithm is improved by 10%. For L2 band data, the results show that the accuracy of snow depth inversion of various algorithms do not change with the variations of snow depth. Among the three single algorithms, the inversion accuracy of FFT algorithm is better than that of LSP and NLSF algorithms.     

聚合物淬火介质CH-202M在钢铁零件淬火上的基础研究

 聚合物淬火介质冷却金属时于金属表面形成一层聚合物隔离膜,45钢和40Cr钢在不同浓度介质中淬火,可得到比水淬、油淬更大的淬透深度和更小的淬火变形,并可防止淬火开裂。淬火后的组织正常,机械性能符合要求。故表明,此种介质用于钢铁零件淬火非常有效。本文还对使用中的一些管理问题进行了阐明。     

电磁波频率和天线深度对水下环天线的影响

海水中的环天线是进行水下电磁通信的主要手段,研究其在空气中产生的场具有重要的实际意义。针对这个问题,建立了3层导电媒质(空气、海水、大地)条件下海水中环天线的辐射模型,得到了空气中电磁场的解析表达式。采用控制变量法,仿真分析了电磁波传播频率和发射天线深度对水下环天线在空气中产生的场的影响,为水下电磁通信的实际应用提供了依据。