Predictive Maintenance of Manned Spacecraft Through Remaining Useful Life Estimation Technique

被引:0
|
作者
CHEN Runfeng [1 ]
YANG Hong [1 ]
机构
[1] Institute of Manned Space System Engineering
关键词
remaining useful life; predictive maintenance; Chinese space station;
D O I
暂无
中图分类号
V467 [航天器的维护与修理];
学科分类号
摘要
Manned spacecraft pose challenges in terms of extremely high safety and reliability, and with the growth of system complexity and longer on-orbit operation time, the traditional management mode, such as monitoring the threshold of parameter passively, is difficult to meet the required safety standards. Predictive maintenance, which analyzes the system heath trend and estimates remaining useful life(RUL) to establish maintenance strategies ahead of time before failure occurs, is a new mode to approach maintenance tasks. Here, a predictive maintenance strategy for complex manned spacecraft is proposed based on the remaining useful life estimation technique. Firstly, a health index is established based on an abundance of telemetry data, reflecting the system’s current health state. Secondly, we map the health index to the remaining useful life through system degradation modelling, taking into consideration both the system’s stochastic deterioration and uncertainty. The maintenance and management strategies are then made based on the calculated distribution of RUL time. Finally, a case study on Chinese space station energy system predictive maintenance is presented.
引用
收藏
页码:3 / 10
页数:8
相关论文
共 50 条
  • [1] A Risk-Averse Remaining Useful Life Estimation for Predictive Maintenance
    Chen, Chuang
    Lu, Ningyun
    Jiang, Bin
    Wang, Cunsong
    IEEE-CAA JOURNAL OF AUTOMATICA SINICA, 2021, 8 (02) : 412 - 422
  • [2] A Risk-Averse Remaining Useful Life Estimation for Predictive Maintenance
    Chuang Chen
    Ningyun Lu
    Bin Jiang
    Cunsong Wang
    IEEE/CAAJournalofAutomaticaSinica, 2021, 8 (02) : 412 - 422
  • [3] Remaining Useful Life Estimation for Predictive Maintenance Using Feature Engineering
    Yurek, Ozlem Ece
    Birant, Derya
    2019 INNOVATIONS IN INTELLIGENT SYSTEMS AND APPLICATIONS CONFERENCE (ASYU), 2019, : 214 - 218
  • [4] On-Line Remaining Useful Life Estimation of Power Connectors Focused on Predictive Maintenance
    Riba, Jordi-Roger
    Gomez-Pau, Alvaro
    Martinez, Jimmy
    Moreno-Eguilaz, Manuel
    SENSORS, 2021, 21 (11)
  • [5] Remaining Useful Life Estimation With Parallel Convolutional Neural Networks On Predictive Maintenance Applications
    Avci, Adem
    Acir, Nurettin
    2020 28TH SIGNAL PROCESSING AND COMMUNICATIONS APPLICATIONS CONFERENCE (SIU), 2020,
  • [6] CoPAL: Conformal Prediction for Active Learning with Application to Remaining Useful Life Estimation in Predictive Maintenance
    Kharazian, Zahra
    Lindgren, Tony
    Magnusson, Sindri
    Bostrom, Henrik
    13TH SYMPOSIUM ON CONFORMAL AND PROBABILISTIC PREDICTION WITH APPLICATIONS, 2024, 230 : 195 - 217
  • [7] Joint Stress Estimation and Remaining Useful Life Prediction for Collaborative Robots to Support Predictive Maintenance
    Kolvig-Raun, Emil Stubbe
    Kjaergaard, Mikkel Baun
    Brorsen, Ralph
    IEEE ROBOTICS AND AUTOMATION LETTERS, 2024, 9 (04): : 3554 - 3561
  • [8] Coevolution of Remaining Useful Lifetime Estimation Pipelines for Automated Predictive Maintenance
    Tornede, Tanja
    Tornede, Alexander
    Wever, Marcel
    Huellermeier, Eyke
    PROCEEDINGS OF THE 2021 GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE (GECCO'21), 2021, : 368 - 376
  • [9] Predictive Maintenance in the Industry: A Comparative Study on Deep Learning-based Remaining Useful Life Estimation
    Lorenti, Luciano
    Pezze, Davide Dalle
    Andreoli, Jacopo
    Masiero, Chiara
    Gentner, Natalie
    Yang, Yao
    Susto, Gian Antonio
    2023 IEEE 21ST INTERNATIONAL CONFERENCE ON INDUSTRIAL INFORMATICS, INDIN, 2023,
  • [10] Predictive Maintenance - Exploring strategies for Remaining Useful Life (RUL) prediction
    Olariu, Eliza Maria
    Portase, Raluca
    Tolas, Ramona
    Potolea, Rodica
    2022 IEEE 18TH INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTER COMMUNICATION AND PROCESSING, ICCP, 2022, : 3 - 8