航空发动机球轴承剥落故障模式分析

为研究航空发动机球轴承的剥落故障模式,利用原子发射光谱技术、自动磨粒分析技术、铁谱技术及能谱分析技术对球 轴承加速等效试验滑油中磨粒的数量、大小、形貌及成分等信息进行分析。结果表明：金属颗粒污染物导致轴承出现初始疲劳剥 落;球轴承剥落的特征磨粒为滚动疲劳磨粒和球形磨粒,内衬套微动磨损的特征磨粒为铁的黑色氧化物和红色氧化铁磨粒;临近 轴承失效时,滑油中Fe元素质量分数由7.49×10 -6 增大至21.74×10 -6 ,特征磨粒数量也由48.9个/mL急剧增加至1433.8个/mL,且特 征磨粒直径主要分布在25～50 μm。金属颗粒污染物的存在使轴承承力内半圈滚道加速出现接触疲劳剥落,滚道剥落到一定程 度后,在轴向力、摩擦力及预紧力等综合作用下在内衬套与承力内半圈接触处发生微动磨损,进一步加剧了滚道的疲劳剥落,最终 导致球轴承失效。     

Sun CubE OnE: A multi-wavelength synoptic solar micro satellite

The Sun cubE onE (SEE) is a 12U CubeSat mission proposed for a phase A/B study to the Italian Space Agency that will investigate Gamma and X-ray fluxes and ultraviolet (UV) solar emission to support studies in Sun-Earth interaction and Space Weather from LEO. More in detail, SEE’s primary goals are to measure the flares emission from soft-X to Gamma ray energy range and to monitor the solar activity in the Fraunhofer Mg II doublet at 280 nm, taking advantage of a full disk imager payload. The Gamma and X-ray fluxes will be studied with unprecedented temporal resolution and with a multi-wavelength approach thanks to the combined use of silicon photodiode and silicon photomultiplier (SiPM) -based detectors. The flare spectrum will be explored from the keV to the MeV range of energies by the same payload, and with a cadence up to 10 kHz and with single-photon detection capabilities to unveil the sources of the solar flares. The energy range covers the same bands used by GOES satellites, which are the standard bands for flare magnitude definition. At the same time SiPM detectors combined with scintillators allow to cover the non-thermal bremsstrahlung emission in the gamma energy range. Given its UV imaging capabilities, SEE will be a key space asset to support detailed studies on solar activity, especially in relation to ultraviolet radiation which strongly interacts with the upper layers of the Earth’s atmosphere, and in relation to space safety, included in the field of human space exploration. The main goal for the UV payload is to study the evolution of the solar UV emission in the Mg II band at two different time scales: yearly variations along the solar cycle and transient variations during flare events. The Mg II index is commonly used as a proxy of the solar activity in the Sun-as-a-star paradigm, in which solar irradiance variations in the UV correlate with the variations in stratospheric ozone concentrations and other physical parameters of the Earth high atmosphere. SEE data will be used together with space and ground-based observatories that provide Solar data (e.g. Solar Orbiter, IRIS, GONG, TSST), high energy particle fluxes (e.g. GOES, MAXI, CSES) and geomagnetic data in a multi-instrument/multi-wavelength/multi-messenger approach.     

X射线脉冲星计时导航应用模式与空间试验进展

结合国家导航体系发展与工程应用迫切需求，主要讨论了X射线脉冲星计时导航的应用模式，并介绍了国内外空间试验进展。总结了脉冲星计时地基射电与空间X射线观测的特点和发展现状，阐释了脉冲星时研究与发展的重要意义；总结并归纳了X射线脉冲星导航的应用特点和现有水平，讨论了X射线脉冲星导航的技术优势和典型应用场景；总结了国内外X射线脉冲星计时导航的空间试验进展。根据国内外的空间试验结果，脉冲星时稳定度可达10-14量级，脉冲星导航精度可达到km量级，初步具备在轨应用价值。因此，加快推进国内脉冲星计时导航技术的在轨演示验证与工程应用具有重要意义。     

Comparison of residual and dense neural network approaches for building extraction from high-resolution aerial images

Applications including change detection, disaster management, and urban planning require precise building information, and therefore automatic building extraction has become a significant research topic. With the improvements in sensor and satellite technologies, more data has become available, and with the increased computational power, deep learning methods have emerged as successful tools. In this study, U-Net and FPN architectures using four different backbones (ResNet-50, ResNeXt-50, SE-ResNext-50, and DenseNet-121), and an Attention Residual U-Net approach were used for building extraction from high-resolution aerial images. Two publicly available datasets, Inria Aerial Image Labeling Dataset and Massachusetts Buildings Dataset were used to train and test the models. According to the results, Attention Residual U-Net model has the highest F1 score with 0.8154, IoU score with 0.7102, and test accuracy with 94.51% on the Inria dataset. On the Massachusetts dataset, FPN Dense-Net-121 model has the highest F1 score with 0.7565 and IoU score with 0.6188, and Attention Residual U-Net model has the highest test accuracy with 92.43%. It has been observed that, FPN with DenseNet backbone can be a better choice when working with small size datasets. On the other hand, Attention Residual U-Net approach achieved higher success when a sufficiently large dataset is provided.     

顾及不确定性分析的多数投票 SAR 影像变化检测

合成孔径雷达（Synthetic Aperture Radar，SAR）影像变化检测是遥感领域的一个重要研究方向。文章以投票法（Majority Voting，MV）为基础，提出一种全新的顾及不确定性分析的SAR影像变化检测方法（Uncertainty Analysis-based MV，UAMV）。首先选取三组典型的差分影像生成算法，生成三组互补的差分影像。然后使用模糊C均值聚类估算每组差分影像的关于变化类和未变化类的模糊隶属度函数。最后用模糊集合和信息熵理论优化MV，构建顾及不确定性分析的多数投票法，并用所构建方法融合三组差分影像的模糊隶属度函数，生成变化检测图。为验证文章方法的有效性，通过三组真实SAR影像数据进行实验分析。实验结果表明：1）通过用信息熵分析MV融合过程中的不确定性，能够显著提高MV的变化检测性能；2）与7种现有相关算法相比，UAMV方法能够取得更优的变化检测结果。该研究为SAR影像变化检测提供一种新的思路和方法。     

Cramér-rao lower bound for pulsar rotation parameters estimation with X-ray pulsar observation data

In this paper, the Cramér-Rao Lower Bound (CRLB) for estimating the rotation parameters of pulsars using X-ray pulsar observation data is deduced, and the calculation equation is presented. In order to verify the correctness of the deduced equation, we use the X-ray pulsar observation data to estimate pulsar rotation parameters, and obtain the root mean square error (RMSE) of the estimated pulsar rotation parameters through conducting repeated experiments. The experimental results suggest that when the observation time increases, the RMSE gradually approaches the estimated CRLB, and that when the observation time is 2.4 × 10⁶ s, the error between the RMSE of pulsar frequency estimation and the CRLB stays at 10^?11 order of magnitude. This verifies that the CRLB expression deduced in this paper is the theoretical lower bound for estimating pulsar rotation parameters. The deduced CRLB in this paper helps determine the minimum variance estimator for pulsar rotation parameter estimation using X-ray pulsar data, providing a benchmark for the comparison between the minimum variance estimator and other estimators.     

Distributed satellite autonomous navigation using X-ray pulsars

Distributed X-ray pulsar-based navigation (DXNAV) is an effective method to realize earth-orbit satellite positioning under weak pulsar signal conditions. In this paper, we propose a new DXNAV method based on multiple information fusion. The DXNAV system principle and the pulse phase estimate Cramér-Rao lower bound are deduced. To suppress the calculation complexity and the error source, the X-ray pulsar photon time-of-arrival detected by each satellite is equivalently converted to the leading satellite directly using the inter-satellite link ranging and starlight angular distance measurement. A high precision estimate model of the pulse phase is built using pulsar standard profile, observed profile, and star-geocentric angular distance from distributed satellites. The estimated pulse phase is real-time supplied to the navigation system, which is established in the form of a deviation equation. The two-stage Kalman filter is designed to estimate the pulse phase in profile histogram bin step and the leader position in real-time step. Compared separately with the maximum likelihood phase estimate method and the celestial navigation method using only the star-geocentric angular distance, the simulation analysis shows that the estimation precisions of position and velocity are improved by 29% and 25%.     

Frequency steering of spaceborne clocks based on XPNAV-1 observations

Due to high stable rotations, timing of pulsars provides a natural tool to correct the frequency deviation of spaceborne atomic clocks. Based on processing the observational data about a year of Crab pulsar given by XPNAV-1 satellite, we study the possibility of correcting the frequency deviation of spaceborne atomic clocks using pulsar timing. According to the observational data in X-ray band and the timing model parameters from radio observations, the pre-fit timing residuals with a level of 6...