An Overview of the State of the Art in Aircraft Prognostic and Health Management Strategies

被引：28
|
作者：
Kordestani, Mojtaba [1 ]
Orchard, Marcos E. [2 ]
Khorasani, Khashayar [3 ]
Saif, Mehrdad [1 ]
机构：
[1] Univ Windsor, Dept Elect & Comp Engn, Windsor, ON N9B 3P4, Canada
[2] Univ Chile, Dept Elect & Comp Engn, Santiago 8370451, Chile
[3] Concordia Univ, Dept Elect & Comp Engn, Montreal, PQ H3G 1M8, Canada
来源：
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT | 2023年 / 72卷
基金：
加拿大自然科学与工程研究理事会;
关键词：
Aircraft; Aircraft propulsion; Prognostics and health management; Turbines; Maintenance engineering; Safety; Fault diagnosis; Aircraft system; failure prognostic; fault detection and isolation (FDI); fault diagnosis; prognostic and health management (PHM); remaining useful life (RUL); REMAINING USEFUL LIFE; FAULT-DETECTION; NEURAL-NETWORK; DATA-DRIVEN; NONLINEAR-SYSTEMS; KALMAN FILTER; PREDICTION; MODEL; DIAGNOSIS; ENSEMBLE;
D O I：
10.1109/TIM.2023.3236342
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
Aircraft are complex engineering systems composed of many interconnected subsystems with possible uncertainties in their structure. They often function for a long number of flight hours under varying or harsh environments. Hence, prognostic and health management (PHM) of critical subsystems or components within the overall system is crucial for maintaining the safety and reliability of the aircraft. This article reviews the state of the art in aircraft failure prognostic. The main definitions and concepts are presented and discussed. In addition, a selected important failure in the representative aircraft components is outlined, and various categories of prognostic strategies are reviewed. Finally, some recommendations and directions for the most promising research to address the PHM problem in aircraft are outlined.
引用
收藏
页数：15
相关论文
共 50 条
  • [21] A review of fault diagnosis, prognosis and health management for aircraft electromechanical actuators
    Yin, Zhengyang
    Hu, Niaoqing
    Chen, Jiageng
    Yang, Yi
    Shen, Guoji
    IET ELECTRIC POWER APPLICATIONS, 2022, 16 (11) : 1249 - 1272
  • [22] Diagnostic and Prognostic Health Management of Electric Vehicle Powertrains : An Empirical Methodology for Induction Motor Analysis
    El Hadraoui, Hicham
    Laayati, Oussama
    El Maghraoui, Adila
    Sabani, Erroumayssae
    Zegrari, Mourad
    Chebak, Ahmed
    2023 5TH GLOBAL POWER, ENERGY AND COMMUNICATION CONFERENCE, GPECOM, 2023, : 153 - 158
  • [23] Exploring Prognostic and Diagnostic Techniques for Jet Engine Health Monitoring: A Review of Degradation Mechanisms and Advanced Prediction Strategies
    De Giorgi, Maria Grazia
    Menga, Nicola
    Ficarella, Antonio
    ENERGIES, 2023, 16 (06)
  • [24] Aircraft engine health prognostics based on logistic regression with penalization regularization and state-space-based degradation framework
    Yu, Jianbo
    AEROSPACE SCIENCE AND TECHNOLOGY, 2017, 68 : 345 - 361
  • [25] Overview of Explainable Artificial Intelligence for Prognostic and Health Management of Industrial Assets Based on Preferred Reporting Items for Systematic Reviews and Meta-Analyses
    Nor, Ahmad Kamal Mohd
    Pedapati, Srinivasa Rao
    Muhammad, Masdi
    Leiva, Victor
    SENSORS, 2021, 21 (23)
  • [26] Robustness of AI-based prognostic and systems health management
    Khan, Samir
    Tsutsumi, Seiji
    Yairi, Takehisa
    Nakasuka, Shinichi
    ANNUAL REVIEWS IN CONTROL, 2021, 51 : 130 - 152
  • [27] A Novel Machine Learning Method Based Approach for Li-Ion Battery Prognostic and Health Management
    Fan, Jiaming
    Fan, Jianping
    Liu, Feng
    Qu, Jiantao
    Li, Ruofeng
    IEEE ACCESS, 2019, 7 : 160043 - 160061
  • [28] Prognostics and Health Management of PEMFC - State of the art and remaining challenges
    Jouin, Marine
    Gouriveau, Rafael
    Hissel, Daniel
    Pera, Marie-Cecile
    Zerhouni, Noureddine
    INTERNATIONAL JOURNAL OF HYDROGEN ENERGY, 2013, 38 (35) : 15307 - 15317
  • [29] Machine Learning Approaches in Battery Management Systems: State of the Art Remaining useful life and fault detection
    Ardeshiri, Reza Rouhi
    Balagopal, Bharat
    Alsabbagh, Amro
    Ma, Chengbin
    Chow, Mo-Yuen
    2020 2ND IEEE INTERNATIONAL CONFERENCE ON INDUSTRIAL ELECTRONICS FOR SUSTAINABLE ENERGY SYSTEMS (IESES), 2020, : 61 - 66
  • [30] Fibromyalgia: state-of-the-art overview
    Choy, Ernest H.
    CLINICAL AND EXPERIMENTAL RHEUMATOLOGY, 2019, 37 (01) : S117 - S117
12345