bluuebunny/crossref_metadata_2025_split huggingface dataset:
Health Assessment of Mission-oriented TT&C Antenna
Authors: Guo Lei , Xu Jihui , He Weihui 
Published: May 2023

Abstract
To solve the problem that it is difficult to quantitatively evaluate the health status of TT&C antennas and that the health status cannot be effectively associated with the ability to perform tasks, this paper proposes a systematic evaluation method for the health management of aerospace TT&C antennas based on the functional mission of TT&C antennas, which closely associates the equipment health status with the ability to perform tasks. According to the functional mission of equipment, the overall health level is evaluated through the health status of the underlying indicators of the ability to perform tasks and equipment performance. Firstly, the assessment index system of the mission-oriented TT&C antenna is analyzed, and then the assessment of the target is decomposed into the assessment of multiple underlying indicators using the analytic hierarchy process (AHP), which is widely used in health assessment. The quantitative assessment is made according to the specific indicators of the lowest level, and their importance to the target assessment is determined layer by layer, so as to achieve the purpose of assessing the target health status. On this basis, the health level of the TT&C antenna is determined according to the maximum membership principle. The evaluation index system and method have important reference significance for the follow-up test and identification work.
Research on WBS-RBS Oriented Security Risk Assessment Index System for Space Domain Private Network
Authors: Wang Rui 
Published: May 2023

Abstract
To solve the problems such as unclear overall situations, incomplete risk analysis, and lack of targeted evaluation indicators of the security of the special network in the aerospace field, this paper takes the special network in the aerospace field as the research object, uses the WBS-RBS method to analyze the risk of network security, and uses the OSM model to establish an evaluation indicator system for the identified risks, to provide an indicator model for the subsequent security detection and evaluation of the special network in the aerospace field.
Fatigue Life Analysis of Bearing in Oscillatory Applications based on Ncode DesignLife
Authors: Ren Hailun , Zhou Aiguo , Jia Jianjun , Li Zhaohui 
Published: May 2023

Abstract
Aiming at the fatigue life of bearing in oscillatory applications, through the analysis of the equivalent load of each part of bearing in oscillatory applications, the equivalent load of each part is calculated. Taking the 7005 angular contact ball bearing as the research object, the stress changes of each component are obtained through the transient dynamic analysis of the model, the fatigue of the bearing is analyzed based on the stress damage theory, and the damage and fatigue life of the bearing is obtained. The results show that the rolling element of the 7005 bearings is the weak part of failure under the given working condition, and it is more reasonable to design the service life of the shafting structure with an equivalent load of the rolling element, which provides reference measures for improving the service life of the oscillated bearing.
Research on flight path planning method based on genetic ant colony algorithm and Maklink diagram
Authors: Bian Xijian , Zhang Kezhi 
Published: May 2023

Abstract
To reduce the cost of a flight, a calculation method is proposed in this paper, which takes the shortest distance as the goal and avoids the obstacle zone, and controls the turning angle as a constraint. Firstly, the Maklink diagram is used to build the obstacle zone model and establish the relationship between the obstacle zones. Then Dijkstra algorithm is used to construct the initial flight path to form a suboptimal path. Then the genetic ant colony algorithm is used to optimize the obtained suboptimal path. When there is a conflict risk between the two planned paths, the flight altitude of the aircraft on one path is adjusted, and the constraints are checked to form the optimal path. The simulation results show that the method can realize flight path optimization and verify the feasibility of the method.
A Space-ground Joint Target Detection System Based on Artificial Intelligence
Authors: Wang Jinghua , Shi Junqing , Lei Yong , Yao Xinyu , Chen Chen , Dong Xiyan 
Published: May 2023

Abstract
Due to the low efficiency and poor adaptability of template matching in target detection, this paper represents a space-ground joint detection system based on artificial intelligence, which takes advantage of the high computation power of the ground system to train neural networks and utilize the measurement and control channel to update and synchronize the on-orbit system. Based on YOLOv5, an oriented bounding box is used for labeling and training, the angle is considered as a class and the loss for the angle is added to the code. After training the network with the ground system, the weight will be sent to the satellite. This process would repeat once there are new training data that worse the update. Based on the new routine for target detection, the accuracy and robustness are significantly higher than before.
Anomaly detection of satellite telemetry data based on extended dominant sets clustering
Authors: Jin Xin , Wang Hui Quan , Jin Zhong He 
Published: May 2023

Abstract
To mine out anomalies in satellite telemetry data under unsupervised conditions, a cluster-based method is proposed in this paper. Firstly, an extended dominant sets clustering algorithm is proposed to cluster the telemetry data with arbitrary shapes. Secondly, objects that do not belong to any cluster or belong to small clusters are traditionally identified as anomalies. Thirdly, the anomalies in large clusters are detected according to the relative similarity. Finally, the information on anomaly windows in the telemetry sequence is obtained according to the local anomaly rate, which provides more characteristics of the anomalies. Experimental results show that: 1) The proposed extended dominant sets clustering algorithm can deal with the dataset containing multiple and arbitrarily shaped clusters; 2) The introduction of relative similarity increases the AUC values of anomaly detection by 3%~10%; 3) The proposed anomaly detection method can effectively detect the anomalies in magnetometer telemetry data of Tianping-2B satellite. Therefore, the proposed method can achieve anomaly detection of satellite telemetry data under unsupervised conditions, and provide support for improving satellite safety and reliability.
Research on Travelling Gust Field Interpolation for Dynamic Response of the Aircraft
Authors: Jing Zhiwei , Wang Libo , Tang Chu 
Published: May 2023

Abstract
The traveling gust by the explosion has a strong influence on the aircraft’s dynamic response. Previous research often takes the hypothesis that the aircraft is ‘frozen’ at the initial location and focuses on the time interpolation of the traveling gust field. This paper investigates the influence of two traveling gust filed interpolation methods on the aircraft dynamic response. The first one is the ‘frozen field’ interpolation method, and the other one is the ‘spatial field’ interpolation method which considers the time and aircraft location. Simulation results demonstrate that the ‘frozen field’ interpolation method increases the dynamic response of the aircraft.
Analysis and application of deep space exploration satellite telemetry data combined with empirical mode decomposition and ARIMA model
Authors: Liu Di , Cui YunFei , Feng Zhuonan , Wang Yanjuan 
Published: May 2023

Abstract
With China’s deep space exploration program constantly expanding, the number of satellites on-orbit is increasing year by year. The stable operation of satellites in orbit hinges on long-term monitoring and analysis of the telemetry data downloaded from the satellite on the ground, which enables quick detection of any irregularities. If we can grasp the changing trend and operation law of satellite telemetry data, we can monitor and control satellites and reduce losses better. Aiming at a large amount of telemetry data of deep space exploration satellites, the data presents non-stationary and nonlinear characteristics, The time series to be processed is constructed sequentially using the acquired telemetry data, and it is decomposed using the empirical mode decomposition approach. The non-stationary signal is divided into a stationary sequence and the sum of a series of stationary intrinsic mode functions. Then the decomposed sets of results are used as the input of the ARIMA model, and the ARIMA model is constructed to predict the predicted value of each decomposed sequence, and the weighted summation of the predicted values is performed to reconstruct the predicted results. Lastly, actual satellite telemetry data is used to confirm the method’s viability. The experimental findings demonstrate that the model can more successfully anticipate the short-term trend of satellite telemetry data.
Spatial-temporal adaptive network partitioning for urban traffic signal control
Authors: Liu Chang , Yuan Hong , Liu Rui , Lin Li , Zhang Yourong , Huang Kaisheng 
Published: May 2023

Abstract
In response to rapidly growing and diversifying traffic demand, it is necessary to develop a network partitioning method that could achieve real-time global optimal performance and adapt to traffic network evolution. In this paper, an adaptive partitioning method is presented, which achieves optimal partitions at runtime and determines appropriate Time-of-Day breakpoints to update partition results simultaneously. For each time interval, partitioning schemes are firstly assessed in terms of modularity by taking roadway geometry, real-time traffic flow information, and signal timing into account. Two values are attained from the assessment: the maximum modularity of the optimal partition and the modularity obtained from the existing partition. Then the existing partition is updated, provided that the relative deviation of these two values exceeds a given threshold for a certain number of successive time intervals. Experimental results show that the above-mentioned partitioning scheme outperforms some notable traffic control techniques in modularity in the spatial aspect. In the temporal aspect, the updating scheme can well respond to varying traffic conditions and yield significantly higher average modularity.
Estimation Distributed Algorithm to Aid Aircraft Runway Scheduling Problem
Authors: Liu Yingli , Hu Minghua , Su Jiaming 
Published: May 2023

Abstract
In this paper, we proposed a runway sequencing and optimal scheduling method. This includes constructing a flight sequencing model to minimize design delay time for arrival and departure flights and designing flight sequencing rules to obtain large-scale feasible runway usage sequences efficiently. Furthermore, a Kendall-τ distance-based Mallows model is constructed based on the obtained flight sequences. An Estimation Distributed Algorithm (EDA) is used to assign each flight a runway usage time that meets the constraint so that the total delay time is minimized. Finally, it is verified that the method can not only reduce the total delay time of the flight as a whole but also has significant performance and is highly implementable through the analysis of calculation cases.
A short-term highway traffic flow forecasting model based on CNN-LSTM with an attention mechanism
Authors: Ma Feihu , Deng Shiqi , Mei Sang 
Published: May 2023

Abstract
Domestic and foreign scholars have researched traffic flow forecasting and established mature systems; however, these systems are mainly based on normal weather. The influence of weather on traffic flow forecasting is rarely considered in existing studies. Therefore, the correlation between meteorology and traffic flow is analyzed, and an attention mechanism is introduced to improve the ability of the model to extract characteristics of time series data. The results show that the model proposed in this paper is better than other models and the traffic flow forecast using meteorological data is more accurate when an attention mechanism is added.
Optimization of holes routing in hydraulic manifold blocks based on simulated annealing algorithm
Authors: Jia Chunqiang , Li Han , Yu Ling 
Published: May 2023

Abstract
The design of the hydraulic manifold block is time-consuming, laborious, and prone to make mistakes due to the vertical intersection and dense complexity of its internal oil passage network. The mathematical optimization model of this problem is given based on the comprehensive analysis of the structural characteristics and design rules of the internal orifices of the hydraulic manifold block. Using the integrated circuit layout algorithm for reference, an optimization design method of a multi-wire mesh channel network based on routing sequence optimization is proposed and verified by an example. The research results show that the optimization of the connection order between multiple wire networks at both ends and the routing order between multiple wire networks in a single-wire network can not only achieve the optimal design of the connectivity of the single-wire network but also ensure the optimal connectivity result of the entire hole network. At the same time, as the bottom core algorithm of the integrated block layout optimization design, it can provide a powerful technical guarantee for improving the integrated block design level, quality, and automation.
Optimal calculation of the operation strategy of a distributed heating system combining wind, solar and electrical energy
Authors: Zhou Ce , Ma Lirong , Liu Peng 
Published: May 2023

Abstract
In this paper, a distributed combined heating system is proposed, composed of an electrically driven air source heat pump (two-stage compression type), solar collector, wind turbine heater, and thermal storage device. A multi-objective optimization mathematical model is established, aiming to minimize the operating cost and carbon dioxide emission during a certain time. The multi-objective planning problem is used to guide solutions to building heating problems in Northern China. Subsequently, for a specific example, the NSGA2 algorithm is used to solve the calculation. Based on the compromise solution of the two optimization objectives, the optimal operation strategy is determined: the amount of heat generated or stored by each device on a typical day. The optimal operating strategy is as follows. In the low heat load period (9:00-16:00), which coincides with the sunny period, the heat production of the solar collectors and the wind turbine heaters exceeds the heat load, and the storage device stores surplus heat. During peak hours (0:00-9:00, 16:00-24:00), the solar collectors are not activated because the solar irradiance is nearly zero. And at this point, the heat production by the wind turbine heaters fluctuates greatly, and the air source heat pump turns out to be the main heating equipment and the heat storage device to release heat when necessary.
Optimal Dispatch of Multi-energy Microgrid Considering Flexible Resources Aggregation
Authors: Xiang Xinyu , Gong Chengyao , Zong Xingchen , Luo Qing , Xia Tian , Lu Tao 
Published: May 2023

Abstract
Distributing energy has facilitated the interaction between electricity, heating, and gas systems. Aggregating flexible resources in the optimal scheduling process of multi-energy microgrids can promote the complementary coordination of multi-energy systems and reduce useless energy waste. In this paper, flexible resource aggregation analysis is added to the optimal scheduling problem of multi-energy microgrids. Firstly, a resource aggregation model based on Mincowski addition is proposed to fully characterize the schedulable potential of flexible resources. Then, a multi-energy microgrid collaborative optimal scheduling model is established to fully exploit the operational potential of flexible resources. Finally, a numerical example is simulated to verify the validity of the aggregation model and control algorithm above-mentioned, which improves the efficiency and accuracy of optimal control of multi-energy microgrids.
The Investigation of the Mixture Formation and Combustion Characteristic of the Spray-wall Impingement
Authors: Li Jingyuan , Wang Xiaoyang , Yu Hanzhengnan , Liu Yu , An Xiaopan , Ma Kunqi , Liang Yongkai , Xu Hang , Zhang Hao 
Published: May 2023

Abstract
In recent years, investigations into the formation of mixture or combustion characteristics of diesel spray-wall impingement have been summarized. On one hand, the air entrainment strength and fuel concentration distribution in the near-wall area during the spray-wall collision process have been studied. On the other hand, the combustion characteristics of the impinged spray, including ignition and combustion characteristics, have also been discussed. Additionally, the effect of impingement between spray and wall on real diesel engines’ operating condition has been analyzed and summarized. Results showed that increasing the pressure of the injection and shortening the collision distance could enhance the air entrainment strength of spray-wall impingement. Moreover, increasing the injection pressure, shortening the impingement distance, decreasing the environmental pressure, increasing the wall temperature, and reducing the nozzle diameter all improved the mixture formation. Conversely, reducing the environmental temperature, decreasing the nozzle diameter, and increasing the impingement distance all reduced the concentration of soot, and even achieved no soot formation. Under real diesel engine operation conditions, some of the soot formed in the spray-wall collision and deposited on the wall. The structure of these deposits was mainly a simple cluster structure composed of several basic particles, and the porous structure of the deposits was conducive to the oxidation of soot and reduced the deposition rate.
Simultaneous analysis of supercritical carbon dioxide power cycle coupling zeotropic organic Rankine cycle with composition-adjustment and dual-pressure evaporation
Authors: Huang Renlong , Chen Chaoda , Wang Yage , Zhong Tianming 
Published: May 2023

Abstract
A novel cycle is established about the supercritical carbon dioxide power cycle (S-CO2) and the zeotropic organic Rankine cycle (ORC). The thermal efficiency of S-CO2 is superior to the steam Rankine cycle. However, the waste heat released from the expander is not well utilized. The zeotropic ORC with dual-pressure evaporation is considered to be one of the most promising cycles for recovering waste heat. Dual-pressure evaporation of ORC can improve the phase change heat transfer matching in the evaporation section, thus improving the energy conversion efficiency. If the composition of the zeotropic mixture can be adjusted during the dual-pressure evaporation process, the system power performance can be further improved. The supercritical carbon dioxide power cycle coupling the zeotropic organic Rankine cycle with composition adjustment and dual-pressure evaporation (S-CO2/ORC) is proposed for energy utilization efficiency. The influence of different working fluids and exergy destruction analysis is carried out for S-CO2/ORC. The results show that the net power output of the system is the largest, which is 359.79 kW, when R245fa-R236ea is used as the working fluid for the ORC. The analysis of the exergy destruction of S-CO2/ORC using R245fa-R236ea shows that the S-CO2 system accounted for the largest exergy destructions.
Max-Pressure Controller for Networks of Signalized Intersection and simulation study
Authors: Xiong Shuai , Zhu Xiaodong , Meng Weiwei , Guo Liping 
Published: May 2023

Abstract
Urban intersections are faced with complex congestion problems and centralized control system has many drawbacks. To solve this problem, a relatively simple local control method - the maximum pressure (MP) control strategy is studied. Meanwhile, the simulation of the proposed MP control method is conducted. After analyzing the simulation results, it is found that MP control can realize the adaptive change of phase duration. The MP control makes the number of throughput vehicles at a high level and can stabilize the queue length within a certain range, ensuring the stability of the operation of the intersection. The control effect of MP is better than that of the fixed-time control.
Active RCD adaptive voltage balancing control strategy for high-voltage uncontrolled rectifier valve
Authors: Chen Wenhao , Yang Ping , Peng Guoping , Liu Zejian , Zeng Jun , Shi Ben , Wang Hongzhan 
Published: May 2023

Abstract
The voltage balance of the series diodes is the premise to ensure the stable and reliable operation of the high voltage uncontrolled rectifier valve. When traditional RC and RCD voltage balancing methods are applied to high voltage uncontrolled rectifier valves in far-reaching offshore wind farms, the complex and changeable operating environment poses a challenge to the anti-interference of the balance effect of the snubber circuit. In this paper, an active RCD adaptive voltage balancing control strategy with strong anti-interference ability is proposed based on the establishment of the active RCD voltage balancing model of the high voltage uncontrolled rectifier valve. The parameter tuning method of the active RCD snubber circuit is given, and the auto-PID control strategy of the active RCD snubber circuit is proposed according to its nonlinear time-varying characteristics. The simulation example verifies that the active RCD adaptive voltage balancing strategy of the high voltage uncontrolled rectifier valve has strong anti-interference performance, which provides a reference for the design of the high voltage uncontrolled rectifier valve voltage sharing system in the far-reaching offshore wind farm.
A Link Real-time Travel Time Estimation on Speed-time Field Traversing Incorporating LSTM Neural Network
Authors: Chen Shiyi , Pan Yiyong 
Published: May 2023

Abstract
A travel time estimation method based on Speed-time field traversal including LSTM neural network was proposed to increase the real-time and accuracy of travel time estimation. The node departure speed of the traditional piecewise truncated quadratic speed trajectory model was optimized by the road node arrival speed, considering the impact of road conditions on travel time. The node arrival speed was modeled as time series and predicted in the short-term future by combining the LSTM neural network model to construct a spatiotemporally continuous speed trajectory, to estimate the link’s travel time. The method was tested on an actual road and gave considerably improved estimates and results compared to the original method, using LSTM neural network to predict node departure speed and the technique using node arrival speed. According to experimental results, the proposed method performs well in both smooth and crowded traffic circumstances, serving as a benchmark for precise real-time travel time estimation on urban roads.