Long Short-Term Memory Network for Integrated Modular Avionics Degradation Modeling and Health Assessment

被引：2

作者：

Guo, Yingchao ^{[1
]}

Chen, Jie ^{[1
]}

Zhong, Yichen ^{[1
]}

Shen, Chi ^{[1
]}

Zhao, Yuyang ^{[1
]}

机构：

[1] Northwestern Polytech Univ, Sch Civil Aviat, Xian, Peoples R China

来源：

2022 IEEE 2ND INTERNATIONAL CONFERENCE ON COMPUTER COMMUNICATION AND ARTIFICIAL INTELLIGENCE (CCAI 2022) | 2022年

关键词：

Integrated Modular Avionics; Long Short-Term Memory; Degradation Modeling; Health Assessment;

D O I：

10.1109/CCAI55564.2022.9807807

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

With the improvement of aircraft informatization, Integrated Modular Avionics (IMA) system has become an important part of modern aircraft airborne systems, and its operation status has great significance to ensure flight safety, therefore, it is necessary to study its degradation process and health assessment. Based on the IMA system analysis and health state classification, the Long Short-Term Memory (LSTM) network is introduced in this paper to model the IMA system's degradation process and assess system health status, the effectiveness of the proposed method for degradation modeling and health assessment is verified by the experimental simulation in the end.

引用

页码：38 / 42

页数：5

共 50 条

[21] Bidirectional Long Short-Term Memory Network for Vehicle Behavior Recognition [J].

Zhu, Jiasong ;

Sun, Ke ;

Jia, Sen ;

Lin, Weidong ;

Hou, Xianxu ;

Liu, Bozhi ;

Qiu, Guoping .

REMOTE SENSING, 2018, 10 (06)

[22] Automatic Fall Detection Using Long Short-Term Memory Network [J].

Magalhaes, Carlos ;

Ribeiro, Joao ;

Leite, Argentina ;

Pires, E. J. Solteiro ;

Pavao, Joao .

ADVANCES IN COMPUTATIONAL INTELLIGENCE, IWANN 2021, PT I, 2021, 12861 :359-371

[23] Credit Risk Assessment Based on Long Short-Term Memory Model [J].

Zhang, Yishen ;

Wang, Dong ;

Chen, Yuehui ;

Shang, Huijie ;

Tian, Qi .

INTELLIGENT COMPUTING THEORIES AND APPLICATION, ICIC 2017, PT II, 2017, 10362 :700-712

[24] Modular Spiking Neural Circuits for Mapping Long Short-Term Memory on a Neurosynaptic Processor [J].

Shrestha, Amar ;

Ahmed, Khadeer ;

Wang, Yanzhi ;

Widemann, David P. ;

Moody, Adam T. ;

Van Essen, Brian C. ;

Qiu, Qinru .

IEEE JOURNAL ON EMERGING AND SELECTED TOPICS IN CIRCUITS AND SYSTEMS, 2018, 8 (04) :782-795

[25] Hybrid long short-term memory and bidirectional multichannel network cascaded with split convolution for short-term load forecasting [J].

Hasanat, Syed Muhammad ;

Ullah, Irshad ;

Aurangzeb, Khursheed ;

Rizwan, Muhammad ;

Alhussein, Musaed ;

Anwar, Muhammad Shahid .

ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE, 2025, 147

[26] Transfer learning applying electrochemical degradation indicator combined with long short-term memory network for flexible battery state-of-health estimation [J].

Kim, Jaeyeong ;

Han, Dongho ;

Lee, Pyeong-Yeon ;

Kim, Jonghoon .

ETRANSPORTATION, 2023, 18

[27] An Enhancement Method Based on Long Short-Term Memory Neural Network for Short-Term Natural Gas Consumption Forecasting [J].

Liu, Jinyuan ;

Wang, Shouxi ;

Wei, Nan ;

Yang, Yi ;

Lv, Yihao ;

Wang, Xu ;

Zeng, Fanhua .

ENERGIES, 2023, 16 (03)

[28] Long Short-Term Memory Bayesian Neural Network for Air Pollution Forecast [J].

Nguyen, Huynh A. D. ;

Ha, Quang P. ;

Duc, Hiep ;

Azzi, Merched ;

Jiang, Ningbo ;

Barthelemy, Xavier ;

Riley, Matthew .

IEEE ACCESS, 2023, 11 :35710-35725

[29] A COMPACT AND CONFIGURABLE LONG SHORT-TERM MEMORY NEURAL NETWORK HARDWARE ARCHITECTURE [J].

Chen, Kewei ;

Huang, Leilei ;

Li, Minjiang ;

Zeng, Xiaoyang ;

Fan, Yibo .

2018 25TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP), 2018, :4168-4172

[30] Chinese Lyrics Generation Using Long Short-Term Memory Neural Network [J].

Wu, Xing ;

Du, Zhikang ;

Zhong, Mingyu ;

Dai, Shuji ;

Liu, Yazhou .

ADVANCES IN ARTIFICIAL INTELLIGENCE: FROM THEORY TO PRACTICE (IEA/AIE 2017), PT II, 2017, 10351 :419-427

← 1 2 3 4 5 →