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    Review on Attitude Determination and Control Methods for Satellite Emergency Recovery
    WANG Zhenhua, YANG Sen, ZHOU Zeya, HE Yikang
    2024(6):675-688, DOI: 10.16356/j.1005-1120.2024.06.001
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    Abstract:
    Once a satellite experiences extreme abnormal conditions， it may face serious consequences such as structural damages， material low-temperature failures， propellant freezing， and even whole satellite failures if it is not rescued in time. Therefore， it is significantly important to study emergency recovery technologies for satellites. The research progress on attitude determination and control technologies during satellite emergency recovery is reviewed in detail. Moreover， the research achievements in the design and implementation of satellite emergency modes are summarized. By synthesizing and analyzing relevant literature， this paper aims to provide reference and guidance for emergency recovery technologies in response to extremely abnormal satellite states.
    Adaptive Super-Twisting Sliding Mode Fault-Tolerant Control of Launch Vehicles with Actuator Faults
    WANG Kejun, ZHOU Zhijie, FENG Zhichao, YANG Ruohan, HU Changhua, XU Hui
    2024(6):689-699, DOI: 10.16356/j.1005-1120.2024.06.002
    [Abstract] (0) [HTML] (0) [PDF 1.35 M] (0)
    Abstract:
    A fault-tolerant control law based on adaptive super-twisting sliding mode control （SMC） is designed for the attitude command tracking problem of a launch vehicle with actuator faults， considering the uncertainties arising from unknown external disturbances， fuel consumption of the launch vehicle， and the perturbation due to the change in rotational inertia caused by tank sloshing， as well as the potential system model changes due to actuator fault and unmodeled dynamics. This control algorithm integrates the super-twisting SMC， the fuzzy logic control， and the adaptive control. First， a super-twisting sliding surface is selected to mitigate the “chattering” phenomenon inherent in SMC， ensuring that the system tracking error converges to zero within a finite time. Second， building upon this sliding surface， the fuzzy logic control is used to approximate the unknown system function， which includes fault information. Adaptive parameters are used to approach the system parameters and enhance disturbance rejection. The stability and finite-time convergence of the launch vehicle attitude tracking control system are verified by the Lyapunov method. Numerical simulations demonstrate the effectiveness and robustness of the proposed adaptive super-twisting SMC algorithm.
    Aggregation-Value-Based Active Sampling Method for Multi-sensor Freeform Surface Measurement and Reconstruction
    CHEN Gengxiang, LI Yingguang, MEHDI-SOUZANI Charyar, LIU Xu
    2024(6):700-709, DOI: 10.16356/j.1005-1120.2024.06.003
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    Abstract:
    Freeform surface measurement is a key basic technology for product quality control and reverse engineering in aerospace field. Surface measurement technology based on multi-sensor fusion such as laser scanner and contact probe can combine the complementary characteristics of different sensors， and has been widely concerned in industry and academia. The number and distribution of measurement points will significantly affect the efficiency of multi-sensor fusion and the accuracy of surface reconstruction. An aggregation-value-based active sampling method for multi-sensor freeform surface measurement and reconstruction is proposed. Based on game theory iteration， probe measurement points are generated actively， and the importance of each measurement point on freeform surface to multi-sensor fusion is clearly defined as Shapley value of the measurement point. Thus， the problem of obtaining the optimal measurement point set is transformed into the problem of maximizing the aggregation value of the sample set. Simulation and real measurement results verify that the proposed method can significantly reduce the required probe sample size while ensuring the measurement accuracy of multi-sensor fusion.
    YOLO-v8 with Multidimensional Attention and Upsampling Fusion for Small Air Target Detection in Radar Images
    JIANG Zhenyu, LI Xiaodong, DU Chen, CHEN An, HAN Yanqiang, LI Jinjin
    2024(6):710-724, DOI: 10.16356/j.1005-1120.2024.06.004
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    Abstract:
    This study presents an innovative approach to improving the performance of YOLO-v8 model for small object detection in radar images. Initially， a local histogram equalization technique was applied to the original images， resulting in a notable enhancement in both contrast and detail representation. Subsequently， the YOLO-v8 backbone network was augmented by incorporating convolutional kernels based on a multidimensional attention mechanism and a parallel processing strategy， which facilitated more effective feature information fusion. At the model’s head， an upsampling layer was added， along with the fusion of outputs from the shallow network， and a detection head specifically tailored for small object detection， thereby further improving accuracy. Additionally， the loss function was modified to incorporate focal-intersection over union （IoU） in conjunction with scaled-IoU， which enhanced the model’s performance. A weighting strategy was also introduced， effectively improving detection accuracy for small targets. Experimental results demonstrate that the customized model outperforms traditional approaches across various evaluation metrics， including recall， precision， F1-score， and the receiver operating characteristic （ROC） curve， validating its efficacy and innovation in small object detection within radar imagery. The results indicate a substantial improvement in accuracy compared to conventional methods such as image segmentation and standard convolutional neural networks.
    Dual-domain Joint Dense Multiple Small Ship Target Detection Algorithm for Spaceborne SAR Images
    JIA Peng, DONG Tiancheng, WANG Taoyang, ZHANG Guo, SHENG Qinghong, LI Jun
    2024(6):725-738, DOI: 10.16356/j.1005-1120.2024.06.005
    [Abstract] (0) [HTML] (0) [PDF 3.77 M] (0)
    Abstract:
    Ship detection via spaceborne synthetic aperture radar （SAR） has become a research hotspot. However， existing small ship detection methods based on the radar signal domain and SAR image features cannot obtain highly accurate results because of the obvious coherent speckle noise at sea and strong reflection interference from near-shore objects. To resolve the above problems， this study proposes a dual-domain joint dense multiple small ship target detection method for spaceborne SAR image that simultaneously detects objects in the image and frequency domains. This method uses an attention mechanism module and algorithm structure adjustments to improve the small ship target feature mining ability. In the frequency-based image generation， extreme signal strength values are detected in the azimuth and range directions， with the results of the two complementing each other to realize dual-domain joint small ship target detection. The comprehensive qualitative and quantitative evaluation results show that the proposed method can attain a final precision rate of 92.25% and achieve accurate results for SAR ship detection in open-sea， coastal， and port area ships. The test results for the self-built SAR small-ship dataset demonstrate the effectiveness and universality of the method.
    Helicopter Maneuver Trajectory Tracking Control Based on Implicit Model and LADRC
    REN Binwu, CUI Zhuangzhuang, XU Yousong, DU Siliang, ZHAO Qijun
    2024(6):739-749, DOI: 10.16356/j.1005-1120.2024.06.006
    [Abstract] (0) [HTML] (0) [PDF 2.45 M] (0)
    Abstract:
    To enhance the stability of helicopter maneuvers during task execution， a composite trajectory tracking controller design based on the implicit model （IM） and linear active disturbance rejection control （LADRC） is proposed. Initially， aerodynamic models of the main and tail rotor are created using the blade element theory and the uniform inflow assumption. Subsequently， a comprehensive flight dynamic model of the helicopter is established through fitting aerodynamic force fitting. Subsequently， for precise helicopter maneuvering， including the spiral， spiral up， and Ranversman maneuver， a regular trim is undertaken， followed by minor perturbation linearization at the trim point. Utilizing the linearized model， controllers are created for the IM attitude inner loop and LADRC position outer loop of the helicopter. Ultimately， a comparison is made between the maneuver trajectory tracking results of the IM-LADRC and the conventional proportional-integral-derivative （PID） control method is performed. Experimental results demonstrate that utilizing the post-trim minor perturbation linearized model in combination with the IM-LADRC method can achieve higher precision in tracking results， thus enhancing the accuracy of helicopter maneuver execution.
    Experimental and Numerical Investigation of Micro Tip Injection in a High-Speed Axial Compressor Rotor
    LIU Wenhao, CHU Wuli, ZHANG Haoguang, WANG Hao, WANG Guang
    2024(6):750-765, DOI: 10.16356/j.1005-1120.2024.06.007
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    Abstract:
    A series of experiments and numerical simulations are carried out in a high-speed axial compressor to systematically investigate the influence and underlying flow mechanisms of micro tip injection on enhancing compressor stability. Different geometric structures of micro tip injection have been investigated， including the axial positions of injector port， injected mass flow rate and injector diameter. First， seven designed micro tip injection structures and one solid wall casing are tested in the compressor test rig to elucidate the influence of different micro tip injection parameters on the compressor stability. Then， numerical simulations are conducted to analyze the underlying flow mechanisms of micro tip injection with different design parameters on enhancing the compressor stability. The experimental and numerical investigation reveal that when the injection port is located upstream of the low-speed region， the compressor stability is significantly enhanced. The tip injection with larger injected mass flow can obtain higher stall margin improvement. Smaller injector diameter produces higher injection momentum and velocity， contributing to greater improvement on the compressor stability.
    Research on Accessibility Factors of Metal Particles and Structural Optimization of Intermediate Gearbox in a Helicopter
    LU Fengxia, WANG Honglin, WEI Kun, LENG Sheng
    2024(6):766-782, DOI: 10.16356/j.1005-1120.2024.06.008
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    Abstract:
    The intermediate gearbox of a helicopter operates under splash lubrication. If the bearing produces metal particles due to insufficient lubrication or wear， whether it can be adsorbed by the metal particles signal at the bottom of the gearbox and alarm directly affects the flight safety of the helicopter. Based on the CFD method， the factors affecting the accessibility of metal particles are analyzed by using the volume of fluid-discrete phase model（VOF-DPM） coupling model， the RNG k-? turbulence model and the dynamic grid technology. Furthermore， the optimization research on the casing structure is conducted. Experimental results show that the accessibility of metal particles is optimal when the gear speed is 6 000 rad/min or the immersion depth is 24 mm. The density of metal particles exhibits a nonlinear relationship with their accessibility， and the particle size has a relatively small impact on their accessibility without an order of magnitude change.
    A Deep Learning-Based Approach for Terminal Area Flight Flow Operational Safety Situation Awareness
    DENG Cheng, ZHANG Qiqian, ZHANG Honghai, WAN Junqiang, LI Jingyu
    2024(6):783-805, DOI: 10.16356/j.1005-1120.2024.06.009
    [Abstract] (0) [HTML] (0) [PDF 5.38 M] (0)
    Abstract:
    Safety is the cornerstone of the civil aviation industry and the enduring focus of civil aviation. This paper uses air traffic complexity and potential aircraft conflict relationships as entry points to study the operational safety level of terminal area flight flows and proposes a deep learning-based method for safety situation awareness in terminal area aircraft operations. Firstly， a more comprehensive and precise safety situation assessment features are constructed. Secondly， a deep clustering situation recognition model with added safety situation information capture layer is proposed. Finally， a spatiotemporal graph convolutional neural network based on attention mechanism is constructed for predicting safety situations. Experimental results from a real dataset show that： （1） The proposed model surpasses traditional models across all evaluated dimensions； （2） the recognition model ensures that the encoded features capture distinctive safety situation information， thereby enhancing model interpretability and task alignment； （3） the prediction model demonstrates superior integrated modeling capabilities in both spatial and temporal dimensions. Ultimately， this paper elucidates the spatiotemporal evolution characteristics of air traffic safety situation levels， offering valuable insights for air traffic safety management.
    Manufacturing Resource Management and Control for Production Site of Complex Products
    CHEN Lin, HUANG Wei, ZHANG Zhengxin, ZHOU Jingyao, HE Jiawei
    2024(6):806-818, DOI: 10.16356/j.1005-1120.2024.06.010
    [Abstract] (0) [HTML] (0) [PDF 2.73 M] (1)
    Abstract:
    In response to the complex composition， scattered data storage， and differences in management levels of manufacturing resources in the production site of complex products， the research and application of digital technology for perception and control of manufacturing resources in the production site of complex products are of great significance for accelerating the digital transformation and upgrading of complex product manufacturing enterprises. Firstly， focusing on the problems of single element of local management， high cost of heterogeneous integration of multiple data sources， and the difficulty in cleaning up the global status of manufacturing resources in the production site of complex products， basic requirements and core requirements of enterprises for global management and control of manufacturing resources in the production site are deeply analyzed. Secondly， the indicators and data sources of different manufacturing resources that managers at different levels are concerned about are analyzed， providing guidance for refined management. Thirdly， a reference architecture of the manufacturing resource management and control platform for the production site of complex products is proposed， supporting access， integration， and global unified management of manufacturing resource information through the access strategy， data， basic component， and APP layers. Finally， the feasibility， effectiveness， and practicality of the architecture are verified through practical cases， aiming to provide a reference for the manufacturing resource management of complex product manufacturing enterprises.
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