With the advancement of digital transformation in distribution substations, a large number of smart devices are being integrated into substations. Addressing the challenges of automatic topology recognition and the issue of unstable recognition accuracy in distribution substations has become crucial. This paper proposes a substation topology recognition method based on an improved matrix approach and the Minimum Conditional Probability of Packet Loss Theorem. The improved matrix approach is utilized to calculate the topological signals, enabling automatic bottom-up topology recognition within the substation. The application of the Minimum Conditional Probability of Packet Loss Theorem in processing topological data significantly enhances the accuracy of substation topology recognition, reducing the impact of external factors on recognition accuracy. Experimental validation demonstrates that the proposed method is highly feasible and exhibits fault tolerance, indicating practical engineering applications.
Water is a vital element for sustaining life on extraterrestrial planets. In this paper, we propose an 80-100 GHz tripler based on a Schottky diode to supply a CubeSat standard 183 GHz THz radiometer for detecting water on outer planets. We introduce the THz anti-parallel Schottky diode and its layout, serving as the core component of the tripler, enabling efficient frequency multiplication in the THz range. The structure of the THz radiometer tripler is presented, explaining its design and functionality. Analysis reveals a conversion loss of 2 dB within the 80-100 GHz frequency range, demonstrating the tripler's efficiency in generating the desired 183 GHz THz frequency for water detection. The successful implementation of this tripler design contributes to the development of a CubeSat-compatible THz radiometer, enhancing our ability to detect and study water on outer planets. This advancement opens new prospects for exploration and potential habitability assessment in outer space.
Since the emergence of COVID-19, there have been many local outbreaks with foci at shopping malls in China. We compared and analyzed the epidemiological and spatiotemporal characteristics of local COVID-19 outbreaks in two commercial locations, a department store building (DSB) in Baodi District, Tianjin, and the Xinfadi wholesale market (XFD) in Fengtai District, Beijing. The spread of the infection at different times was analyzed by the standard deviation elliptical method. The spatial transfer mode demonstrated that outbreaks started at the center of each commercial location and spread to the periphery. The number of cases and the distance from the central outbreak showed an inverse proportional logarithmic function shape. Most cases were distributed within a 10 km radius; infected individuals who lived far from the outbreak center were mainly infected by close-contact transmission at home or in the workplace. There was no efficient and rapid detection method at the time of the DSB outbreak; the main preventative measure was the timing of COVID-19 precautions. Emergency interventions (closing shopping malls and home isolation) were initiated five days before confirmation of the first case from the shopping center. In contrast, XFD closed after the first confirmed cases appeared, but those infected during this outbreak benefitted from efficient nucleic acid testing. Quick results and isolation of infected individuals were the main methods of epidemic control in this area. The difference in the COVID-19 epidemic patterns between the two shopping malls reflects the progress of Chinese technology in the prevention and control of COVID-19.
Recent advancements have revolutionized interplanetary spacecraft missions by combining low-thrust propulsion systems with planetary Gravity-Assist (GA) maneuvers. This study investigates/improved a novel dual-step efficient-robust homotopy algorithm, grounded in indirect optimal control principles, to analyze fuel-optimal bang-bang control problems. The methodology integrates efficient techniques, including the homotopic method, compatible normalization, and improved switching function detection, aimed at enhancing optimal convergence in solving low-thrust gravity-assist spacecraft missions. To illustrate practical application, an Earth-to-Jupiter interplanetary scenario utilizing Mars-GA is examined. Results demonstrate the algorithm's superior efficacy in achieving fuel efficiency, robust convergence, and remarkable accuracy compared to existing solutions.
In this paper, a novel statistical metric learning is developed for spectral-spatial classification of the hyperspectral image. First, the standard variance of the samples of each class in each batch is used to decrease the intra-class variance within each class. Then, the distances between the means of different classes are used to penalize the inter-class variance of the training samples. Finally, the standard variance between the means of different classes is added as an additional diversity term to repulse different classes from each other. Experiments have conducted over two real-world hyperspectral image datasets and the experimental results have shown the effectiveness of the proposed statistical metric learning.
The deconvolution technique can improve the spatial resolution of Millimeter and Sub-millimeter Sounding/Imager (MMSI) of FY-4 satellite. In this paper, the technique is applied to the simulated brightness temperature image of a typhoon scene, which indicates that the deconvolution technique is feasible to enhance the spatial resolution of MMSI. In the analysis of the antenna temperature of the earth obtained by MMSI, We consider the effect of beam scanning and acquire an accurate estimate of the brightness temperature distribution. The results show that the outline of the typhoon in the enhanced image is closer to the initial image than the non-enhanced image. The correlation coefficient is improved and the spatial resolution is enhanced from 96km to 57km, which indicates the effectiveness.
We present the design, simulation, and measurement of a polarization-independent and angle-insensitive metamaterial absorber (MA) in X-band. Since the unit cell of the MA consists of four subwavelength split-ring resonators with 4-fold symmetric rotation, the MA is insensitive to the variation of both polarization and incident angle of the planar electromagnetic wave. The electromagnetic performances of the MA are studied by full-wave simulations based on finite-element method and the Naval Research Laboratory arch experimental measurements. The electric field distributions are numerically investigated, which confirm the polarization-insensitive property of the MA, as expected from the symmetric nature of the structure. When the incident angles vary from 0 to 45 degrees, the MA remains at full width at half maximum of 0.4 GHz (0.5 GHz) with peak absorptions of 99.9% (95.2%) at 10.27 GHz (10.3 GHz) by simulations (measurements).
Under some specific conditions,the line fault could possibly cause the transformer fault and exert serious consequence.Taking an inter-phase fault as an example,which is caused by lightning stroke and leads to the insulation damage of 110 kV transformer,this paper analyzes the causes of transformer's insulation damage specifically in respects of inspection of onsite situation,analysis on protective action,inspection and test of transformer,and presents the corresponding preventive measures during repair and maintenance of the related electric installation,targeting the fault causes.
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