A robust object-based shadow detection method for cloud-free high resolution satellite images over urban areas and water bodies

Unwanted contrast in high resolution satellite images such as shadow areas directly affects the result of further processing in urban remote sensing images. Detecting and finding the precise position of shadows is critical in different remote sensing processing chains such as change detection, image classification and digital elevation model generation from stereo images. The spectral similarity between shadow areas, water bodies, and some dark asphalt roads makes the development of robust shadow detection algorithms challenging. In addition, most of the existing methods work on pixel-level and neglect the contextual information contained in neighboring pixels. In this paper, a new object-based shadow detection framework is introduced. In the proposed method a pixel-level shadow mask is built by extending established thresholding methods with a new C₄ index which enables to solve the ambiguity of shadow and water bodies. Then the pixel-based results are further processed in an object-based majority analysis to detect the final shadow objects. Four different high resolution satellite images are used to validate this new approach. The result shows the superiority of the proposed method over some state-of-the-art shadow detection method with an average of 96% in F-measure.     

Characterization of ionospheric amplitude scintillations using wavelet entropy detrended GNSS data

The extensive monitoring networks of Global Navigation Satellite System (GNSS) ionospheric scintillation have been established to continuously log observation data. Further, the amplitude scintillation index and the phase scintillation index, which are derived from scintillation observations, are anticipated to accommodate the accuracy requirement of both the user level and the monitoring station level. However, raw scintillation observations essentially measure superposed waveform impairments of GNSS signals propagating through ionosphere and troposphere. It implies that fluctuations of raw scintillation observations are caused by multiple factors from the entire radio propagation environment. Hence, it is crucial to characterize ionospheric scintillations from GNSS observation data. And the characterization is implemented through extracting fluctuations of raw observations merely induced by ionospheric scintillations. Designed to address this problem by means of Fourier filtering detrending, the present work investigates the influence of varying detrending cutoff frequencies on wavelet statistical energy and wavelet entropy distributions of scintillation data. It consequently derives criteria on the optimum detrending cutoff frequency for three types of raw amplitude scintillation data, which are classified by their wavelet energy distributions. Results of the present work verify that detrending with specific optimum cutoff frequencies rather than the fixed and universally applicable one renders the validity and credibility of characterizing ionospheric scintillations as the part of GNSS observation fluctuations purely induced by ionosphere electron density irregularities whose scale sizes are comparable with or smaller than the Fresnel scale.     

Д-30发动机ЭИ868合金扇形块的钎焊修复

针对某Д-30发动机大修对ЭИ868合金(对应于我国的牌号GH3044)扇形块的修复要求,采用真空钎焊的方法对扇形块进行了钎焊补焊。对钎焊补焊的扇形块进行超声波探伤。结果表明,钎缝内部质量满足HB7575-97一级钎焊接头的要求,表明所确定的修复工艺可实现ЭИ868合金扇形块的可靠修复。     

分组级短码长LT喷泉码的工程应用

针对LT喷泉码在准单向链路、高差错、链路恶劣易中断的信道环境应用时出现的运算量大、译码时延长、编码效率较低等问题,文章提出使用基于数据分块的分组级短码长喷泉码方案。其思想是将短码长LT码方案和分组级LT码方案结合起来,并且在数据子块的度序列生成过程中加入度值检测机制。实验仿真结果表明:与已提出的LT码方案相比,该方案能够有效地降低译码开销、计算代价和译码时延,提高系统的最大传输效率。     

便携式充电设备检测系统的研究与设计

为了便于充电设备现场检测工作,设计了一种便携式直流充电设备现场检测系统。该系统功能具有完善的测试功能,能够方便的对直流充电设备进行检验测试,完全满足直流充电设备运行检测的需求。该系统具有小型化、便携化的优点,有利于提高现场检测效率,保证了充电设备运行的安全性及稳定性。     

SF6分解气的近红外在线检测技术研究

为满足SF6绝缘电气设备故障监测与预警的实际需求,分析了国内分解气检测研究现状.对比近红外与中红外吸收光谱检测技术,提出近红外吸收光谱技术在线检测的技术方案.计算分析待测气体特征谱线的吸收系数、吸收光程和电路信噪比对精度的影响,完成系统参数设计.提出SF6分解气在线检测系统方案,实现对H2S、HF和CO这3种气体测量.数据分析表明,系统检测精度优于5×10-7,表明该系统满足电力行业在线测量的需求.     

机载无源侦察定位方法研究

无源侦察定位是电子对抗的重要组成部分,在隐身与反隐身、电子侦察等方面的作用日益突出.介绍了飞机侦察定位所采用的测向方法,并对两种常用的测向方法进行了精度分析,给出了装备飞机的应用建议.     

Multi-mode diagnosis of a gas turbine engine using an adaptive neuro-fuzzy system

Gas Turbine Engines (GTEs) are vastly used for generation of mechanical power in a wide range of applications from airplane propulsion systems to stationary power plants. The gas-path components of a GTE are exposed to harsh operating and ambient conditions, leading to several degradation mechanisms. Because GTE components are mostly inaccessible for direct measurements and their degradation levels must be inferred from the measurements of accessible parameters, it is a challenge to acquire reliable information on the degradation conditions of the parts in different fault modes. In this work, a data-driven fault detection and degradation estimation scheme is developed for GTE diagnostics based on an Adaptive Neuro-Fuzzy Inference System (ANFIS). To verify the performance and accuracy of the developed diagnostic framework on GTE data, an ensemble of measurable gas path parameters has been generated by a high-fidelity GTE model under (a) diverse ambient conditions and control settings, (b) every possible combination of degradation symptoms, and (c) a broad range of signal to noise ratios. The results prove the competency of the developed framework in fault diagnostics and reveal the sensitivity of diagnostic results to measurement noise for different degradation symptoms.     

Semi-stochastic modification of second-order radial derivative of Abel–Poisson’s formula for validating satellite gravity gradiometry data

The geoid can be used to validate the satellite gravity gradiometry data. Validation of such data is important prior to their downward continuation because of amplification of the data errors through this process. In this paper, the second-order radial derivative of Abel–Poisson’s formula is modified stochastically to reduce the effect of the far-zone geoid and generate the second-order radial derivative of geopotential at 250 km level. The numerical studies over Fennoscandia show that this method yields the gradients with an error of 10 mE and when the long wavelength of geoid is removed from the estimator and restored after the computations (remove–compute–restore) the error will be in 1 mE level. We name this method semi-stochastic modification. The best case scenario is found when the degree of modification of the integral formula is 200 and the long wavelength geoid to degree 100 is removed and restored. In this case the geoid should have a resolution of 15′ × 15′ and the integration should be performed over a cap size of 3°.     

Automatic detection of geomagnetic sudden commencement via time–frequency clusters

One of global processes in ionosphere–thermosphere–magnetosphere system is the geomagnetic storms. It is of great importance to develop an algorithm that auto-detects sudden commencement because it could be an indicator of onset of the geomagnetic storm. Automatic detection of geomagnetic sudden commencement is based on time–frequency clusters generated by spectrogram. Proposed algorithm is tested on data set collected from stations belong to the international real-time magnetic observatory network (INTERMAGNET). Maximum standard deviation of algorithm detection times is observed to be one minute of the corresponding arrival times published by National Geophysical Data Center (NGDC).