Intelligent Health Management of Fixed-Wing UAVs: A Deep-Learning-based Approach

Aiya Cui; Ying Zhang; Pengyu Zhang; Wei Dong; Chunyan Wang

doi:10.1109/ICARCV50220.2020.9305491

Intelligent Health Management of Fixed-Wing UAVs: A Deep-Learning-based Approach

Aiya Cui
, Ying Zhang
, Pengyu Zhang
, Wei Dong
, Chunyan Wang

Beijing Institute of Technology
Peking University
China Aerospace Science and Technology Corporation

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

12 引用（Scopus）

摘要

In this paper, the fault diagnosis and health management of fixed-wing UAVs are investigated based on the deep learning technique. The proposed method includes 5 models: flight data generation model, sample training prediction model based on the Long Short-Term Memory (LSTM) network, prediction model based on the grey model, combined prediction model and health calculation and management model. The realtime output of the health prediction value of the fixed-wing UAVs can be obtained, which makes it possible to take remedial action before the fault occurs. And numerical simulations demonstrate the feasibility of the proposed method.

源语言	英语
主期刊名	16th IEEE International Conference on Control, Automation, Robotics and Vision, ICARCV 2020
出版商	Institute of Electrical and Electronics Engineers Inc.
页	1055-1060
页数	6
ISBN（电子版）	9781728177090
DOI	https://doi.org/10.1109/ICARCV50220.2020.9305491
出版状态	已出版 - 13 12月 2020
已对外发布	是
活动	16th International Conference on Control, Automation, Robotics and Vision, ICARCV 2020 - Virtual, Online, 中国期限: 13 12月 2020 → 15 12月 2020

丛书

姓名	16th IEEE International Conference on Control, Automation, Robotics and Vision, ICARCV 2020

会议

会议	16th International Conference on Control, Automation, Robotics and Vision, ICARCV 2020
国家/地区	中国
市	Virtual, Online
时期	13/12/20 → 15/12/20

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10.1109/ICARCV50220.2020.9305491

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引用此

Cui, A., Zhang, Y., Zhang, P., Dong, W., & Wang, C. (2020). Intelligent Health Management of Fixed-Wing UAVs: A Deep-Learning-based Approach. 在 16th IEEE International Conference on Control, Automation, Robotics and Vision, ICARCV 2020 (页码 1055-1060). 期刊论文 9305491 (16th IEEE International Conference on Control, Automation, Robotics and Vision, ICARCV 2020). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICARCV50220.2020.9305491

Cui, Aiya ; Zhang, Ying ; Zhang, Pengyu 等. / Intelligent Health Management of Fixed-Wing UAVs : A Deep-Learning-based Approach. 16th IEEE International Conference on Control, Automation, Robotics and Vision, ICARCV 2020. Institute of Electrical and Electronics Engineers Inc., 2020. 页码 1055-1060 (16th IEEE International Conference on Control, Automation, Robotics and Vision, ICARCV 2020).

@inproceedings{2cb0610f1a444340ac3453759b18a320,

title = "Intelligent Health Management of Fixed-Wing UAVs: A Deep-Learning-based Approach",

abstract = "In this paper, the fault diagnosis and health management of fixed-wing UAVs are investigated based on the deep learning technique. The proposed method includes 5 models: flight data generation model, sample training prediction model based on the Long Short-Term Memory (LSTM) network, prediction model based on the grey model, combined prediction model and health calculation and management model. The realtime output of the health prediction value of the fixed-wing UAVs can be obtained, which makes it possible to take remedial action before the fault occurs. And numerical simulations demonstrate the feasibility of the proposed method.",

author = "Aiya Cui and Ying Zhang and Pengyu Zhang and Wei Dong and Chunyan Wang",

note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 16th International Conference on Control, Automation, Robotics and Vision, ICARCV 2020 ; Conference date: 13-12-2020 Through 15-12-2020",

year = "2020",

month = dec,

day = "13",

doi = "10.1109/ICARCV50220.2020.9305491",

language = "English",

series = "16th IEEE International Conference on Control, Automation, Robotics and Vision, ICARCV 2020",

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

pages = "1055--1060",

booktitle = "16th IEEE International Conference on Control, Automation, Robotics and Vision, ICARCV 2020",

address = "United States",

}

Cui, A, Zhang, Y, Zhang, P, Dong, W & Wang, C 2020, Intelligent Health Management of Fixed-Wing UAVs: A Deep-Learning-based Approach. 在 16th IEEE International Conference on Control, Automation, Robotics and Vision, ICARCV 2020., 9305491, 16th IEEE International Conference on Control, Automation, Robotics and Vision, ICARCV 2020, Institute of Electrical and Electronics Engineers Inc., 页码 1055-1060, 16th International Conference on Control, Automation, Robotics and Vision, ICARCV 2020, Virtual, Online, 中国, 13/12/20. https://doi.org/10.1109/ICARCV50220.2020.9305491

Intelligent Health Management of Fixed-Wing UAVs: A Deep-Learning-based Approach. / Cui, Aiya; Zhang, Ying; Zhang, Pengyu 等.
16th IEEE International Conference on Control, Automation, Robotics and Vision, ICARCV 2020. Institute of Electrical and Electronics Engineers Inc., 2020. 页码 1055-1060 9305491 (16th IEEE International Conference on Control, Automation, Robotics and Vision, ICARCV 2020).

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

TY - GEN

T1 - Intelligent Health Management of Fixed-Wing UAVs

T2 - 16th International Conference on Control, Automation, Robotics and Vision, ICARCV 2020

AU - Cui, Aiya

AU - Zhang, Ying

AU - Zhang, Pengyu

AU - Dong, Wei

AU - Wang, Chunyan

PY - 2020/12/13

Y1 - 2020/12/13

N2 - In this paper, the fault diagnosis and health management of fixed-wing UAVs are investigated based on the deep learning technique. The proposed method includes 5 models: flight data generation model, sample training prediction model based on the Long Short-Term Memory (LSTM) network, prediction model based on the grey model, combined prediction model and health calculation and management model. The realtime output of the health prediction value of the fixed-wing UAVs can be obtained, which makes it possible to take remedial action before the fault occurs. And numerical simulations demonstrate the feasibility of the proposed method.

AB - In this paper, the fault diagnosis and health management of fixed-wing UAVs are investigated based on the deep learning technique. The proposed method includes 5 models: flight data generation model, sample training prediction model based on the Long Short-Term Memory (LSTM) network, prediction model based on the grey model, combined prediction model and health calculation and management model. The realtime output of the health prediction value of the fixed-wing UAVs can be obtained, which makes it possible to take remedial action before the fault occurs. And numerical simulations demonstrate the feasibility of the proposed method.

UR - https://www.scopus.com/pages/publications/85100093759

U2 - 10.1109/ICARCV50220.2020.9305491

DO - 10.1109/ICARCV50220.2020.9305491

M3 - Conference contribution

AN - SCOPUS:85100093759

T3 - 16th IEEE International Conference on Control, Automation, Robotics and Vision, ICARCV 2020

SP - 1055

EP - 1060

BT - 16th IEEE International Conference on Control, Automation, Robotics and Vision, ICARCV 2020

PB - Institute of Electrical and Electronics Engineers Inc.

Y2 - 13 December 2020 through 15 December 2020

ER -

Cui A, Zhang Y, Zhang P, Dong W, Wang C. Intelligent Health Management of Fixed-Wing UAVs: A Deep-Learning-based Approach. 在 16th IEEE International Conference on Control, Automation, Robotics and Vision, ICARCV 2020. Institute of Electrical and Electronics Engineers Inc. 2020. 页码 1055-1060. 9305491. (16th IEEE International Conference on Control, Automation, Robotics and Vision, ICARCV 2020). doi: 10.1109/ICARCV50220.2020.9305491

Intelligent Health Management of Fixed-Wing UAVs: A Deep-Learning-based Approach

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