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[1]杨述明,谢昌霖,程玉强,等.液体火箭发动机健康监控技术研究进展[J].火箭推进,2024,50(01):28-45.[doi:10.3969/j.issn.1672-9374.2024.01.003]
　YANG Shuming,XIE Changlin,CHENG Yuqiang,et al.Research progress in health monitoring technology for liquid rocket engines[J].Journal of Rocket Propulsion,2024,50(01):28-45.[doi:10.3969/j.issn.1672-9374.2024.01.003]
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液体火箭发动机健康监控技术研究进展

《火箭推进》[ISSN:1672-9374/CN:CN 61-1436/V] 卷: 50 期数: 2024年01期 页码: 28-45 栏目: 目次 出版日期: 2024-02-28
Title:
Research progress in health monitoring technology for liquid rocket engines
文章编号:
1672-9374(2024)01-0028-18
作者:
杨述明; 谢昌霖; 程玉强; 宋立军
国防科技大学 空天科学学院,湖南 长沙 410073
Author(s):
YANG Shuming;  XIE Changlin;  CHENG Yuqiang;  SONG Lijun
College of Aerospace Science and Engineering, National University of Defense Technology,Changsha 410073, China
关键词:
液体火箭发动机;  健康监控技术;  故障检测与诊断;  容错控制;  健康监控系统
Keywords:
liquid rocket engine;  health monitoring technology;  fault detection and diagnosis;  fault tolerant control;  health monitoring system
分类号:
V434
DOI:
10.3969/j.issn.1672-9374.2024.01.003
文献标志码:
A
摘要:
液体火箭发动机健康监控技术作为保障运载火箭安全、可靠发射的核心关键技术,经过几十年的发展,有力推动了航天事业的进步。介绍了液体火箭发动机健康监控技术中故障检测与诊断、容错控制与健康监控系统研制等技术的研究现状与发展趋势; 梳理了健康监控领域面临的重难点问题,并提出相应的解决方案。分析展望了液体火箭发动机健康监控技术未来发展趋势,为从事火箭发动机健康监控技术研究的科研人员提供参考。
Abstract:
Liquid rocket engine health monitoring technology, as the core and key technology to ensure the safe and reliable launch of carrier rockets, has vigorously promoted the progress of space industry after decades of development. This paper introduces the research status and development trends of fault detection and diagnosis, fault-tolerant control and health monitoring system in liquid rocket engine health monitoring technology. The important and difficult problems in the field of health monitoring are sorted out, and corresponding solutions are put forward. Finally, the future development trends of liquid rocket engine health monitoring technology is analyzed and prospected, which provides some references for the researchers engaged in the research of rocket engine health monitoring technology.

参考文献/References:

[1] 新华社.我国最大推力液体火箭发动机首次整机试车圆满成功[EB/OL].[2022-11-05].https://www.ayrbs.com/szb/pad/content/202211/07/content_16415.html.
[2]YANG S M, XIE C L, CHENG Y Q, et al.Autonomous attitude reconstruction analysis for propulsion system with typical thrust drop fault[J].Aerospace,2022,9(8): 409.
[3]吴建军,张育林,陈启智.液体火箭发动机健康监控技术[J].宇航学报,1995,16(2): 93-99.
WU J J,ZHANG Y L,CHEN Q Z.Health monitoring technology of liquid rocket engine[J].Journal of Astronautics, 1995, 16(2): 93-99.
[4]WEI Z.Failure characteristics analysis and fault diagnosis for liquid rocket engines[M].[S.l.]: Springer Publishing Company, Incorporated, 2016.
[5]ZHU X B, CAI Z, WU J J, et al.Convolutional neural network based combustion mode classification for condition monitoring in the supersonic combustor[J].Acta Astronautica, 2019, 159: 349-357.
[6]DENG L Z, CHENG Y Q, SHI Y H.Fault detection and diagnosis for liquid rocket engines based on long short-term memory and generative adversarial networks[J].Aerospace,2022,9(8): 399.
[7]FRANK P M, DING X.Survey of robust residual generation and evaluation methods in observer-based fault detection systems[J].Journal of Process Control, 1997, 7(6): 403-424.
[8]YU H H, WANG T.A method for real-time fault detection of liquid rocket engine based on adaptive genetic algorithm optimizing back propagation neural network[J].Sensors, 2021, 21(15): 5026.
[9]GAO Z W, CECATI C, DING S X.A survey of fault diagnosis and fault-tolerant techniques. Part I: Fault diagnosis with model-based and signal-based approaches[J].IEEE Transactions on Industrial Electronics, 2015, 62(6): 3757-3767.
[10]DUYAR A, ELDEM V, MERRILL W, et al.Fault detection and diagnosis in propulsion systems:a fault parameter estimation approach[J].Journal of Guidance Control Dynamics, 1994, 17(1): 104-108.
[11]DAVIDSON M,STEPHENS J.Advanced health management system for the space shuttle main engine[C]//40th AIAA/ASME/SAE/ASEE Joint Propulsion Conference and Exhibit.Reston, Virigina: AIAA, 2004.
[12]CHA J,HA C,KO S,et al.Application of fault factor method to fault detection and diagnosis for space shuttle main engine[J].Acta Astronautica, 2016, 126: 517-527.
[13]吴建军,张育林,陈启智.液体火箭发动机基于模型的故障检测算法[J].国防科技大学学报, 1994, 16(4): 8-15.
WU J J, ZHANG Y L, CHEN Q Z.Model-based fault detection algorithm for liquid rocket engine[J].Journal of National University of Defense Technology, 1994, 16(4): 8-15.
[14]BUTAS J, MEYER C,SANTI L, et al.Rocket engine health monitoring using a model-based approach[C]//37th Joint Propulsion Conference and Exhibit.Reston, Virigina: AIAA,2001.
[15]CHA J, KO S, PARK S Y, et al.Fault detection and diagnosis algorithms for transient state of an open-cycle liquid rocket engine using nonlinear Kalman filter methods[J].Acta Astronautica, 2019, 163: 147-156.
[16]BERNARDI E, ADAM E J.Observer-based fault detection and diagnosis strategy for industrial processes[J].Journal of the Franklin Institute, 2020, 357(14): 10054-10081.
[17]ISERMANN R.Model-based fault-detection and diagnosis-status and applications[J].Annual Reviews in Control, 2005, 29(1): 71-85.
[18]朱明清.基于Modelica的液体火箭推进系统故障仿真及系统实现[D].武汉: 华中科技大学, 2016.
ZHU M Q.Fault simulation and software development of liquid rocket propulsion system based on modelica[D].Wuhan: Huazhong University of Science and Technology, 2016.
[19]DAVIDSON M, STEPHENS J. Advanced health management system for the space shuttle main engine[C]//40th AIAA/ASME/SAE/ASEE Joint Propulsion Conference and Exhibit.Reston, Virigina: AIAA, 2006.
[20]KAWATSU K, TSUTSUMI S, HIRABAYASHI M, et al.Model-based fault diagnostics in an electromechanical actuator of reusable liquid rocket engine[C]//AIAA Scitech 2020 Forum.Reston, Virginia: AIAA, 2020.
[21]晏政.航天器推进系统基于定性模型的故障诊断方法研究[D].长沙: 国防科学技术大学, 2013.
YAN Z.Investigation on model-based fault diagnosis methods for spacecraft propulsion system[D].Changsha: National University of Defense Technology, 2013.
[22]MODESITT K L.Inductive knowledge acquisition experience with commercial tools for space shuttle main engine testing[R].N90-27326, 1990.
[23]BICKMORE T, BICKFORD R.Aerojet's titan health assessment expert system[C]//28th Joint Propulsion Conference and Exhibit.Reston, Virigina: AIAA, 1992.
[24]GUO T H.An SSME pressure oxidizer turbopump diagnostic system using G2TM real-time expert system[R].N92-13717, 1992.
[25]XIE G J, YAN S Q, TANG Z Y, et al.A PHM system for AEW radar based on AOPS-LSSVM prognostic algorithm and expert knowledge database[C]//2010 Prognostics and System Health Management Conference.Macao, China: IEEE, 2010.
[26]李恺钦.基于改进遗传算法的航空发动机故障诊断专家系统[D].南昌: 南昌航空大学,2012.
LI K Q.Based on an improved genetic algorithm for aero engine fault diagnosis expert system[D].Nanchang: Nanchang Hangkong University, 2012.
[27]WU J.Liquid-propellant rocket engines health-monitoring: a survey[J].Acta Astronautica, 2005, 56(3): 347-356.
[28]HAWMAN M W,GALINAITIS W S,TULPULE S,et al.Framework for a space shuttle main engine health monitoring system[R].NASA-CR-185224, 1990.
[29]朱恒伟,王克昌,陈启智.液体火箭发动机地面试车故障检测的自适应阈值算法[J].推进技术, 2000, 21(1): 1-4.
ZHU H W, WANG K C, CHEN Q Z.Adaptive thresholds algorithm for fault detection of liquid rocket engine in ground test[J].Journal of Propulsion Technology, 2000, 21(1): 1-4.
[30]李艳军.新一代大推力液体火箭发动机故障检测与诊断关键技术研究[D].长沙: 国防科学技术大学,2014.
LI Y J.Study on key techniques of fault detection and diagnosis for new generation large-scale liquid-propellant rocket engines[D].Changsha: National University of Defense Technology, 2014.
[31]FENG Z G, XU T.Comparison of SOM and PCA-SOM in fault diagnosis of ground-testing bed[J].Procedia Engineering, 2011, 15: 1271-1276.
[32]高鸣,任海峰,胡小平,等.独立分量分析在液体火箭发动机故障诊断中的应用[J].导弹与航天运载技术,2013(4): 74-77.
GAO M, REN H F, HU X P, et al.Independent component analysis for fault diagnosis of the liquid rocket engine[J].Missiles and Space Vehicles, 2013(4): 74-77.
[33]HU L, HU N Q, ZHANG X P, et al.Novelty detection methods for online health monitoring and post data analysis of turbopumps[J].Journal of Mechanical Science and Technology, 2013, 27(7): 1933-1942.
[34]AISWARYA N, SUJA PRIYADHARSINI S, MONI K S.An efficient approach for the diagnosis of faults in turbo pump of liquid rocket engine by employing FFT and time-domain features[J].Australian Journal of Mechanical Engineering, 2018, 16(3): 163-172.
[35]杨懿,陈文丽,王永鹏,等.基于Hilbert-Huang变换的液体火箭发动机涡轮泵故障分析[J].清华大学学报(自然科学版),2022,62(3): 540-548.
YANG Y, CHEN W L, WANG Y P, et al.Fault analyses of liquid rocket engine turbopumps based on Hilbert-Huang transforms[J].Journal of Tsinghua University(Science and Technology), 2022, 62(3): 540-548.
[36]杨懿,于涛,郭亚男,等.脉动压力测量技术在火箭发动机试验中的应用[J].宇航学报,2021,42(7): 917-926.
YANG Y, YU T, GUO Y N, et al.Application of fluctuating pressure measurement technology in rocket engine test[J].Journal of Astronautics, 2021, 42(7): 917-926.
[37]王建波,于达仁.液体火箭发动机泄漏故障诊断的信息融合技术[J].航空动力学报,2001,16(1): 38-40.
WANG J B, YU D R.Leak fault diagnosis of liquid rocket engine based on data fusion[J].Journal of Aerospace Power, 2001, 16(1): 38-40.
[38]ZHANG X W, LI H S.Research on transformer fault diagnosis method and calculation model by using fuzzy data fusion in multi-sensor detection system[J].Optik, 2019, 176: 716-723.
[39]LIU Y W,CHENG Y Q, ZHANG Z Z, et al.Multi-information fusion fault diagnosis based on KNN and improved evidence theory[J].Journal of Vibration Engineering & Technologies, 2022, 10(3): 841-852.
[40]陈禛怡,訾艳阳,张晓光,等.一种缓变与速变信号的时间跟踪特征级融合方法: CN115809408A[P].2023-03-17.
[41]WHEELER K,DHAWAN A, MEYER C.SSME sensor modeling using radial basis function neural networks[C]//30th Joint Propulsion Conference and Exhibit.Reston, Virigina: AIAA, 1994.
[42]XU L, ZHAO S B, LI N N, et al.Application of QGA-BP for fault detection of liquid rocket engines[J].IEEE Transactions on Aerospace and Electronic Systems, 2019, 55(5): 2464-2472.
[43]SINGH M K,SUBASH S N, CROSS S A, et al.Liquid propellant rocket engine test data machine learning for error identification[J].Journal of Mechanical and Aeronautical Engineering Research, 2019, 2(2): 53-57.
[44]黄敏超,张育林,陈启智.动态神经网络在液体火箭发动机故障检测与分离中的应用[J].航空动力学报,1996,11(2): 38-41.
HUANG M C, ZHANG Y L, CHENG Q Z.Application of dynamic neural necworks in fault deteetion and separation of liqnid rocket ergines[J].Journal of Aerospace Power, 1996, 11(2): 38-41.
[45]WHITEHEAD B, KIECH E, ALI M.Rocket engine diagnostics using neural networks[C]//26th Joint Propulsion Conference.Reston, Virigina: AIAA, 1990.
[46]孙成志,闫晓东.基于神经网络和证据理论的火箭发动机故障诊断[J].宇航总体技术,2020,4(4): 20-30.
SUN C Z, YAN X D.Fault diagnosis of rocket engine based on neural network and evidence theory[J].Astronautical Systems Engineering Technology, 2020, 4(4): 20-30.
[47]SCHWABACHER M, OZA N, MATTHEWS B.Unsupervised anomaly detection for liquid-fueled rocket propulsion health monitoring[J].Journal of Aerospace Computing, Information, and Communication, 2009, 6(7): 464- 482.
[48]王仲生,姜洪开,徐一艳.发动机转子系统早期故障智能诊断[J].航空学报,2009,30(2): 242-246.
WANG Z S, JIANG H K, XU Y Y.Early fault intelligent diagnosis of aero-engine rotor systems[J].Acta Aeronautica et Astronautica Sinica, 2009, 30(2): 242-246.
[49]KRIZHEVSKY A, SUTSKEVER I, HINTON G E.ImageNet classification with deep convolutional neural networks[C]//International Conference on Neural Information Processing Systems.[S.l.]: Curran Associates Inc, 2012.
[50]ZHU X, CAI Z,WU J, et al.Convolutional neural network based combustion mode classification for condition monitoring in a supersonic combustor[C]//International Astronautical Congress.[S.l.]: [s.n.], 2018.
[51]ZHU X B, CHENG Y Q, WU J J, et al.Steady-state process fault detection for liquid rocket engines based on convolutional auto-encoder and one-class support vector machine[J].IEEE Access, 2020, 8: 3144-3158.
[52]PARK S Y, AHN J.Deep neural network approach for fault detection and diagnosis during startup transient of liquid-propellant rocket engine[J].Acta Astronautica, 2020, 177: 714-730.
[53]李泽东,李志农,陶俊勇,等.基于特征融合的注意力增强卷积神经网络的航空发动机滚动轴承故障诊断方法[J].兵工学报,2022,43(12): 3228-3239.
LI Z D, LI Z N, TAO J Y, et al.Fault diagnosis for aero-engine rolling bearings based on an attention augmented convolutional neural network with feature fusion[J].Acta Armamentarii, 2022, 43(12): 3228-3239.
[54]DENG L, CHENG Y, YANG S, et al.Fault detection and diagnosis for liquid rocket engines with sample imbalance based on wasserstein generative adversarial nets and multilayer perceptron[J].Proceedings of the iMeche, Part G: Journal of Aerospace Engineering, 2023, 237(8): 1751-1763.
[55]LIANG P F, DENG C, WU J, et al.Single and simultaneous fault diagnosis of gearbox via a semi-supervised and high-accuracy adversarial learning framework[J].Knowledge-Based Systems, 2020, 198: 105895.
[56]袁烨,黄虹,程骋,等.基于特征注意力机制的GRU-GAN航空发动机剩余寿命预测[J].中国科学(技术科学),2022,52(1): 198-212.
YUAN Y, HUANG H, CHENG C, et al.Remaining useful life prediction of the aircraft engine based on the GRU-GAN network with a feature attention mechanism[J].Scientia Sinica(Technologica), 2022, 52(1): 198-212.
[57]张晟斐,李天梅,胡昌华,等.基于深度卷积生成对抗网络的缺失数据生成方法及其在剩余寿命预测中的应用[J].航空学报,2022,43(8): 225708.
ZHANG S F, LI T M, HU C H, et al.Missing data generation method and its application in remaining useful life prediction based on deep convolutional generative adversarial network[J].Acta Aeronautica et Astronautica Sinica, 2022, 43(8): 225708.
[58]HE X, TAN S J, WU Z G, et al.Mission reconstruction for launch vehicles under thrust drop faults based on deep neural networks with asymmetric loss functions[J].Aerospace Science and Technology, 2022, 121: 107375.
[59]WEI C Z, WANG M Z, LU B G, et al.Accelerated Landweber iteration based control allocation for fault tolerant control of reusable launch vehicle[J].Chinese Journal of Aeronautics, 2022, 35(2): 175-184.
[60]SONG Z Y, LIU Y, HE Y, et al.Autonomous mission reconstruction during the ascending flight of launch vehicles under typical propulsion system failures[J].Chinese Journal of Aeronautics, 2022, 35(6): 211-225.
[61]LI T, JIANG Z Y, YANG H B, et al.Reconfigurable fault-tolerant control for supersonic missiles with actuator failures under actuation redundancy[J].Chinese Journal of Aeronautics, 2020, 33(1): 324-338.
[62]程堂明,李家文,陈宇,等.运载火箭伺服机构故障检测与诊断的扩展多模型自适应方法[J].国防科技大学学报,2017,39(5): 80-89.
CHENG T M, LI J W, CHEN Y, et al.Extended multiple model adaptive method for fault detection and diagnosis of launch vehicle's servo mechanism[J].Journal of National University of Defense Technology, 2017, 39(5): 80-89.
[63]SHEN Q, WANG D W, ZHU S Q, et al.Finite-time fault-tolerant attitude stabilization for spacecraft with actuator saturation[J].IEEE Transactions on Aerospace and Electronic Systems, 2015, 51(3): 2390-2405.
[64]GAO Z F, ZHOU Z P, QIAN M S, et al.Active fault tolerant control scheme for satellite attitude system subject to actuator time-varying faults[J].IET Control Theory & Applications, 2018, 12(3): 405-412.
[65]TANG P, LIN D F, ZHENG D, et al.Observer based finite-time fault tolerant quadrotor attitude control with actuator faults[J].Aerospace Science and Technology, 2020, 104: 105968.
[66]朱海洋,吴燕生,容易,等.适应有限故障的运载火箭神经网络自适应容错控制[J].西北工业大学学报,2020,38(3): 668-676.
ZHU H Y, WU Y S, RONG Y, et al.A neural network adaptive fault-tolerant control method for launch vehicles with the limited faults[J].Journal of Northwestern Polytechnical University, 2020, 38(3): 668-676.
[67]梁小辉,胡昌华,周志杰,等.基于自适应动态规划的运载火箭智能姿态容错控制[J].航空学报,2021,42(4): 524915.
LIANG X H, HU C H, ZHOU Z J, et al.ADP-based intelligent attitude fault-tolerant control for launch vehicles[J].Acta Aeronautica et Astronautica Sinica, 2021, 42(4): 524915.
[68]CAO T, GONG H J, CHENG P, et al.A novel learning observer-based fault-tolerant attitude control for rigid spacecraft[J].Aerospace Science and Technology, 2022, 128: 107751.
[69]李东,李平岐.长征五号火箭技术突破与中国运载火箭未来发展[J].航空学报,2022,43(10): 527269.
LI D,LI P Q.Technological breakthroughs of LM-5 and future developments of China's launch vehicle[J].Acta Aeronautica et Astronautica Sinica, 2022, 43(10): 527269.
[70]程玉强,崔孟瑜,谢昌霖,等.运载火箭推力下降后的控制力矩重构分析[J].火箭推进,2023,49(1): 21-28.
CHENG Y Q, CUI M Y, XIE C L, et al.Analysis on control torque reconstruction of launch vehicle after thrust drop[J].Journal of Rocket Propulsion, 2023,49(1): 21-28.
[71]包为民,祁振强,张玉.智能控制技术发展的思考[J].中国科学(信息科学),2020,50(8): 1267-1272.
BAO W M, QI Z Q, ZHANG Y.Thoughts on the development of intelligent control technology[J].Scientia Sinica(Informationis), 2020, 50(8): 1267-1272.
[72]吴建军,程玉强,崔星.液体火箭发动机健康监控技术研究现状[J].上海航天(中英文),2020,37(1): 1-10.
WU J J, CHENG Y Q, CUI X.Research status of the health monitoring technology for liquid rocket engines[J].Aerospace Shanghai(Chinese & English), 2020, 37(1): 1-10.
[73]FIORUCCI T R, LAKIND R I, REYNOLDS T D.Advanced engine health management application of the SSME real-time vibration monitoring system[C]//36th AIAA Joint Propulsion Conference.[S.l.]: [s.n.], 2000.
[74]FIGUEROA F.Tutorial integrated systems health management(ISHM): Enabling Intelligent Systems[C]//NASA Conference on Adaptive Hardware and Systems.[S.l.]: [s.n.],2011.
[75]ZHOU J X, XIAO Y T, LIU K, et al.Preliminary analysis for a two-stage-to-orbit reusable launch vehicle[C]//20th AIAA International Space Planes and Hypersonic Systems and Technologies Conference.Reston, Virginia: AIAA,2015.
[76]中国日报.2023年宇航领域科学问题和技术难题发布[EB/OL].[2023-04-24].https://baijiahao.baidu.com/s?id=1764059893653861872&wfr=spider&for=pc.
[77]YANG S M, QIU J, LIU G J.Hierarchical model-based approach to testability modeling and analysis for PHM of aerospace systems[J].Journal of Aerospace Engineering, 2014, 27(1): 131-139.
[78]董雷霆,周轩,赵福斌,等.飞机结构数字孪生关键建模仿真技术[J].航空学报,2021,42(3): 023981.
DONG L T, ZHOU X, ZHAO F B, et al.Key technologies for modeling and simulation of airframe digital twin[J].Acta Aeronautica et Astronautica Sinica, 2021, 42(3): 023981.
[79]SHAFTO M, CONROY M, DOYLE R, et al.Modeling, simulation, information technology & processing roadmap[C]//National and Space Administration.[S.l.:s.n.],2010.
[80]聂蓉梅,周潇雅,肖进,等.数字孪生技术综述分析与发展展望[J].宇航总体技术,2022,6(1): 1-6.
NIE R M, ZHOU X Y, XIAO J, et al.Analysis and perspective on digital twin technology[J].Astronautical Systems Engineering Technology, 2022, 6(1): 1-6.
[81]付洋,曹宏瑞,郜伟强,等.数字孪生驱动的航空发动机涡轮盘剩余寿命预测[J].机械工程学报,2021,57(22): 106-113.
FU Y, CAO H R, GAO W Q, et al.Digital twin driven remaining useful life prediction for aero-engine turbine discs[J].Journal of Mechanical Engineering, 2021, 57(22): 106-113.
[82]WANG M M, FENG S Z, INCECIK A, et al.Structural fatigue life prediction considering model uncertainties through a novel digital twin-driven approach[J].Computer Methods in Applied Mechanics and Engineering, 2022, 391: 114512.
[83]中国科学技术协会.中国科协发布2022重大科学问题、工程技术难题和产业技术问题[EB/OL].[2022-06-27].https://baijiahao.baidu.com/s?id=1736778539121324210&wfr=spider&for=pc.
[84]ZHANG X F, ZHUO L, PENG J, et al.Fault prediction for electromechanical equipment based on spatial-temporal graph information[J].IEEE Transactions on Industrial Informatics, 2022(99): 1.
[85]BRITO L C,SUSTO G A, BRITO J N, et al.An explainable artificial intelligence approach for unsupervised fault detection and diagnosis in rotating machinery[J].Mechanical Systems and Signal Processing, 2022, 163: 108105.
[86]TOLOMEI G, SILVESTRI F.Generating actionable interpretations from ensembles of decision trees[J].IEEE Transactions on Knowledge and Data Engineering, 2021, 33(4): 1540-1553.
[87]STAFF F E.An interview with Dr.Raj Reddy on artificial intelligence[J].Frontiers of Information Technology & Electronic Engineering, 2018, 19(1): 3-5.

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备注/Memo

收稿日期:2023- 11- 14 修回日期:2023- 12- 15
基金项目:国家自然科学基金创新群体研究项目(T2221002)
作者简介:杨述明(1982—),男,博士,副教授,研究领域为液体火箭发动机健康监控。
通信作者:程玉强(1979—),男,博士,研究员,研究领域为液体火箭发动机健康监控。

更新日期/Last Update: 1900-01-01