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

Yingchao Guo; Jie Chen; Yichen Zhong; Chi Shen; Yuyang Zhao

doi:10.1109/CCAI55564.2022.9807807

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

Yingchao Guo, Jie Chen, Yichen Zhong, Chi Shen, Yuyang Zhao

航海学院

Northwestern Polytechnical University Xian

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

1 引用（Scopus）

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.

源语言	英语
主期刊名	2022 IEEE 2nd International Conference on Computer Communication and Artificial Intelligence, CCAI 2022
出版商	Institute of Electrical and Electronics Engineers Inc.
页	38-42
页数	5
ISBN（电子版）	9781665496636
DOI	https://doi.org/10.1109/CCAI55564.2022.9807807
出版状态	已出版 - 2022
活动	2nd IEEE International Conference on Computer Communication and Artificial Intelligence, CCAI 2022 - Beijing, 中国期限: 6 5月 2022 → 8 5月 2022

出版系列

姓名	2022 IEEE 2nd International Conference on Computer Communication and Artificial Intelligence, CCAI 2022

会议

会议	2nd IEEE International Conference on Computer Communication and Artificial Intelligence, CCAI 2022
国家/地区	中国
市	Beijing
时期	6/05/22 → 8/05/22

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10.1109/CCAI55564.2022.9807807

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引用此

Guo, Y., Chen, J., Zhong, Y., Shen, C., & Zhao, Y. (2022). Long Short-Term Memory Network for Integrated Modular Avionics Degradation Modeling and Health Assessment. 在 2022 IEEE 2nd International Conference on Computer Communication and Artificial Intelligence, CCAI 2022 (页码 38-42). (2022 IEEE 2nd International Conference on Computer Communication and Artificial Intelligence, CCAI 2022). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CCAI55564.2022.9807807

Guo, Yingchao ; Chen, Jie ; Zhong, Yichen 等. / Long Short-Term Memory Network for Integrated Modular Avionics Degradation Modeling and Health Assessment. 2022 IEEE 2nd International Conference on Computer Communication and Artificial Intelligence, CCAI 2022. Institute of Electrical and Electronics Engineers Inc., 2022. 页码 38-42 (2022 IEEE 2nd International Conference on Computer Communication and Artificial Intelligence, CCAI 2022).

@inproceedings{dfa3bdfea1b2450aa1dbc927f5a7ff9e,

title = "Long Short-Term Memory Network for Integrated Modular Avionics Degradation Modeling and Health Assessment",

abstract = "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.",

keywords = "Degradation Modeling, Health Assessment, Integrated Modular Avionics, Long Short-Term Memory",

author = "Yingchao Guo and Jie Chen and Yichen Zhong and Chi Shen and Yuyang Zhao",

note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 2nd IEEE International Conference on Computer Communication and Artificial Intelligence, CCAI 2022 ; Conference date: 06-05-2022 Through 08-05-2022",

year = "2022",

doi = "10.1109/CCAI55564.2022.9807807",

language = "英语",

series = "2022 IEEE 2nd International Conference on Computer Communication and Artificial Intelligence, CCAI 2022",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "38--42",

booktitle = "2022 IEEE 2nd International Conference on Computer Communication and Artificial Intelligence, CCAI 2022",

}

Guo, Y, Chen, J, Zhong, Y, Shen, C & Zhao, Y 2022, Long Short-Term Memory Network for Integrated Modular Avionics Degradation Modeling and Health Assessment. 在 2022 IEEE 2nd International Conference on Computer Communication and Artificial Intelligence, CCAI 2022. 2022 IEEE 2nd International Conference on Computer Communication and Artificial Intelligence, CCAI 2022, Institute of Electrical and Electronics Engineers Inc., 页码 38-42, 2nd IEEE International Conference on Computer Communication and Artificial Intelligence, CCAI 2022, Beijing, 中国, 6/05/22. https://doi.org/10.1109/CCAI55564.2022.9807807

Long Short-Term Memory Network for Integrated Modular Avionics Degradation Modeling and Health Assessment. / Guo, Yingchao; Chen, Jie; Zhong, Yichen 等.
2022 IEEE 2nd International Conference on Computer Communication and Artificial Intelligence, CCAI 2022. Institute of Electrical and Electronics Engineers Inc., 2022. 页码 38-42 (2022 IEEE 2nd International Conference on Computer Communication and Artificial Intelligence, CCAI 2022).

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

TY - GEN

T1 - Long Short-Term Memory Network for Integrated Modular Avionics Degradation Modeling and Health Assessment

AU - Guo, Yingchao

AU - Chen, Jie

AU - Zhong, Yichen

AU - Shen, Chi

AU - Zhao, Yuyang

PY - 2022

Y1 - 2022

N2 - 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.

AB - 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.

KW - Degradation Modeling

KW - Health Assessment

KW - Integrated Modular Avionics

KW - Long Short-Term Memory

UR - http://www.scopus.com/inward/record.url?scp=85134395911&partnerID=8YFLogxK

U2 - 10.1109/CCAI55564.2022.9807807

DO - 10.1109/CCAI55564.2022.9807807

M3 - 会议稿件

AN - SCOPUS:85134395911

T3 - 2022 IEEE 2nd International Conference on Computer Communication and Artificial Intelligence, CCAI 2022

SP - 38

EP - 42

BT - 2022 IEEE 2nd International Conference on Computer Communication and Artificial Intelligence, CCAI 2022

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2nd IEEE International Conference on Computer Communication and Artificial Intelligence, CCAI 2022

Y2 - 6 May 2022 through 8 May 2022

ER -

Guo Y, Chen J, Zhong Y, Shen C, Zhao Y. Long Short-Term Memory Network for Integrated Modular Avionics Degradation Modeling and Health Assessment. 在 2022 IEEE 2nd International Conference on Computer Communication and Artificial Intelligence, CCAI 2022. Institute of Electrical and Electronics Engineers Inc. 2022. 页码 38-42. (2022 IEEE 2nd International Conference on Computer Communication and Artificial Intelligence, CCAI 2022). doi: 10.1109/CCAI55564.2022.9807807

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

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