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| 1 | Trajectory prediction of ballistic missiles using Gaussian process error model显示文摘Ballistic Missile Trajectory Prediction(BMTP)is critical to air defense systems.Most Trajectory Prediction(TP)methods focus on the coast and reentry phases,in which the Ballistic Missile(BM)trajectories are modeled as ellipses or the state components are propagated by the dynamic integral equations on time scales.In contrast,the boost-phase TP is more challenging because there are many unknown forces acting on the BM in this phase.To tackle this difficult problem,a novel BMTP method by using Gaussian Processes(GPs)is proposed in this paper.In particular,the GP is employed to train the prediction error model of the boost-phase trajectory database,in which the error refers to the difference between the true BM state at the prediction moment and the integral extrapolation of the BM state.And the final BMTP is a combination of the dynamic equation based numerical integration and the GP-based prediction error.Since the trained GP aims to capture the relationship between the numerical integration and the unknown error,the modified BM state prediction is closer to the true one compared with the original TP.Furthermore,the GP is able to output the uncertainty information of the TP,which is of great significance for determining the warning range centered on the predicted BM state.Simulation results show that the proposed method effectively improves the BMTP accuracy during the boost phase and provides reliable uncertainty estimation boundaries. | Ruiping JI Yan LIANG Linfeng XU Zhenwei WEI | 2022 | Chinese Journal of Aeronautics2022，35，1： | 3 |
| 2 | 机器学习算法在重型燃气轮机健康监测的应用现状显示文摘重型燃气轮机是提供电力和调节电力波动的重要设备,其组成复杂、精密程度高,发生故障后会产生严重的安全隐患,进而影响经济效益。采用机器学习算法是实现重型燃气轮机健康监测的有效方法。机器学习算法的优化及融合对重型燃气轮机系统的健康运行具有重大意义。介绍了重型燃气轮机健康监测的发展过程;综述了采用不同机器学习算法对燃气轮机大部件及其子部件健康诊断的预测结果;重点分析对比了气路故障和整体状态健康监测、寿命预测的不同方法;总结燃气轮机健康监测的主要技术问题及展望未来的发展方向,为机器学习算法在重型燃气轮机的应用提供了参考。 | 许未晴 冀守虎 安永伟 贾冠伟 曹鑫源 王佳 蔡茂林 吴素君 | 2023 | 液压与气动2023，47，4： | 2 |
| 3 | SAR performance-based fault diagnosis for electrohydraulic control system:A novel FDI framework for closed-loop system显示文摘Model-based fault diagnosis serves as an efficient and powerful technique in addressing fault detection and isolation(FDI)issues for control systems.However,the standard methods and their modifications still encounter some difficulties in algorithm design and application for complex higher-order systems.To avoid these difficulties,a novel fault diagnosis framework based on multiple performance indicators of closed-loop control system is proposed.Under this framework,a socalled performance residual vector is constructed to measure the differences between the real system and the nominal model in terms of system stability,accuracy,and rapidity(SAR)respectively.The criteria for quantification,normalization of the SAR residuals and the explicit mappings between the thresholds and the required performance are given.FDI can be easily achieved simultaneously by monitoring the normalized residual vector length and direction in the SAR performance residual space.A case study on electro-hydraulic servo control system of turbofan engine is adopted to demonstrate the effectiveness of the proposed method. | Yang ZHANG Shaoping WANG Jian SHI Xinyu YANG Jiarui ZHANG Xi WANG | 2022 | Chinese Journal of Aeronautics2022，35，10： | 0 |
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