Software tool for evaluation of reliability and survivability of complex technical system based on logical-probabilistic methodology

The paper presents solutions for estimation and analysis of complex system (CS) reliability and survivability indicators based on the logical-probabilistic approach. Modified logical-probabilistic method and software tool for evaluating the reliability and survivability of onboard equipment (OE) of small satellites were developed (SS). The correctness of the suggested method and software tool was shown by computational experiments on some systems of CS SS similar to Belarusian SS, and later compared with the “Arbitr” software complex results.

RADIATION EFFECTS IN INTEGRATED CHIPS WHEN EXPOSED TO IONIZING RADIATION

In the onboard equipment, components of electronics, which have increased sensitivity to the effects of ionizing radiation are widely used. The transient processes in electronic products are particularly dangerous, associated with an absorbed dose of radiation, leading to functional or irre-versible failures in the operation of onboard systems.

Analysis of Fabricability of Flexible Waveguide Parts for Satellite Applications

Satellite onboard equipment includes waveguide transmission lines. One of the tasks to be solved is the temperature decoupling of the waveguide path and onboard equipment devices. In order to prevent waveguide path deformation during expansion/contraction due to thermal effects, the waveguide is equipped with a flexible waveguide section capable of changing the length without deteriorating radio technical characteristics. The paper considers the issues of fabrication of flexible waveguide parts, concerning the requirements for structure, properties, heat treatment of raw materials, dimensions of workpieces, equipment, and tooling. Within the study, we optimized and tested in practice operations of the technological process of extracting parts from sheet material, rolling, profiling, and shaping, which make it possible to manufacture parts of waveguide paths of the required quality.

Calibration of Onboard Equipment for Measuring Pseudo-Range Between Spacecraft to Improve the Accuracy of Determining Their Time Scales Discrepancy

Technologies for range-finding measurements between spacecraft are increasingly used in achieving the targets of modern spacecraft. The stability of the systematic error is one of the main factors affecting the accuracy of achieving a target. This determines the requirement to ensure the stability of the systematic error at the level of several centimeters in the presence of destabilizing factors and a tendency to increase the spacecrafts active life in orbit. Apart from searching for methods implemented directly in the onboard equipment, it is advisable to consider mathematical methods that are applicable at the stage of processing measurements when achieving the spacecraft targets. The paper describes the technology for determining and accounting for calibration corrections for spacecraft onboard radio-technical equipment intended for range-finding measurements and exchanging information between spacecraft. This technology is based on statistical processing of residuals of linear combinations of measured parameters relative to their high-precision calculated analogs, obtained using a posteriori ephemeris-time information. The use of this technology makes it possible to compensate for the change in the constant component of the systematic measurement error at the stage of spacecraft operation in orbit.

An Edge Computing-Enabled Train Obstacle Detection Method Based on YOLOv3

Rail transit is developing towards intelligence which takes lots of computation resource to perform deep learning tasks. Among these tasks, object detection is the most widely used, like track obstacle detection, catenary wear, and defect detection and looseness detection of train wheel bolts. But the limited computation capability of the train onboard equipment prevents running deep and complex detection networks. The limited computation capability of the train onboard equipment prevents conducting complex deep learning tasks. Cloud computing is widely utilized to make up for the insufficient onboard computation capability. However, the traditional cloud computing architecture will bring in uncertain heavy traffic load and cause high transmission delay, which makes it fail to complete real-time computing intensive tasks. As an extension of cloud computing, edge computing (EC) can reduce the pressure of cloud nodes by offloading workloads to edge nodes. In this paper, we propose an edge computing-based method. The onboard equipment on a fast-moving train is responsible for acquiring real-time images and completing a small part of the inference task. Edge computing is used to help execute the object detection algorithm on the trackside and carry most of the computing power. YOLOv3 is selected as the object detection model, since it can balance between the real-time and accurate performance on object detection compared with two-stage models. To save onboard equipment computation resources and realize the edge-train cooperative interface, we propose a model segmentation method based on the existing YOLOv3 model. We implement the cooperative inference scheme in real experiments and find that the proposed EC-based object detection method can accomplish real-time object detection tasks with little onboard computation resources.

Neural network analysis of telemetry data of on-board equipment of space crafts

Goal. Research and development of methodology and software tools of machine automated analysis of telemetry data of onboard equipment (OE) of space crafts (SC). Research methods. The developed software tools and methodology are based on the machine learning, neural networks and image processing methods and algorithms. Results. The paper presents solutions for the actual tasks of machine analysis of telemetry data of OE SC with the purpose of detecting the states of its functioning and analyzing the reliability and operability. Software tools and methodology of neural network clustering-classification analysis of OE SC telemetry data based on the application of the neural networks such as the Kohonen SOM and image processing methods have been developed. The software tools were implemented in desktop and web versions and has a flexible modular service-oriented architecture. Conclusion. The presented software tools and the methodology of neural network analysis of OE SC telemetry data were tested on real telemetry data of the Belarusian spacecraft and the SC group AIST and showed the results with a confidence probability value of at least 0.9. The proposed tools of neural network analysis of the OE SC telemetry data make it possible to develop recommendations for improving the indicators of OE SC reliability during design and operation, detecting the OE SC states, making the correct control and operational decisions of the ground control complex. Key words: neural network, Kohonen SOM, image processing, modular service-oriented architecture, machine neural network telemetry data analysis, onboard equipment of space crafts.

Stages of information support of development of on-board equipment for spacecraft

The ground-experimental testing of the elements of space technology is a crucial stage in the creation of space products, in fact, this is the ground «flight» of the devices being created. And how well the operating conditions will be reproduced at this stage and the successful functioning of the devices under the expected conditions is ensured, its successful operation in real flight during the service life depends. The radio electronic devices of the onboard equipment of the spacecraft are one of the essential elements that ensure the fulfillment of target tasks, which should confirm their readiness for the forthcoming work at the stage of groundbased experimental testing. The article discusses the stages of information support for the development of spacecraft onboard equipment, showing the ways to improve the technology of ground-based experimental testing of spacecraft onboard equipment. It is shown that at the present stage of development of the space industry, it has become possible to introduce the methodology of mathematical planning of an experiment into engineering practice. A backlog of applied work on radio-electronic topics h as appeared, showing the possibility of revealing in a full factorial experiment the influence of internal uncontrollable parameters (factors) of electronic components on the experimental results. This removed the obstacle to the implementation of the capabilities of the method in research and improvement of radio electronic devices onboard equipment.

Assessment of the resistance of technical means of space systems and complexes to the effects of electrostatic discharges

In order to further improve the methods of protecting the onboard spacecraft equipment from the effects ofelectrostatic discharges, based on a comprehensive study of the problem of the occurrence of electrostatic discharges, theauthors carried out the studies described in this article to analyze the functioning of the onboard spacecraft equipment under the influence of electrostatic discharges. In the course of the research, the methodology for assessing the resistance ofthe onboard equipment of the spacecraft to the effects of electrostatic discharges was refined, based on the generalization of the calculation and analytical work. The analysis of the resistance of the onboard equipment of the spacecraft was carried out taking into account the main mechanisms of the effect of electrostatic discharges on the onboard space network. Taking into account the need to assess the resistance of the onboard space network equipment to electrostatic discharges outside real operating conditions, the authors assess the resistance of the onboard space network equipment on the basis of mathematical and physical modeling. Asaresult of the study, an algorithm was developed for assessing the resistance of the onboard equipment of a spacecraft to the effects of electrostatic discharges, which is described in detail in this article.