Study on the method of thermal prediction for electronic wing pod cabin

Yang Chao; Pang Liping; Wang Jun; Zhou Yue; Qu Hongquan

doi:10.1109/IECON.2017.8216717

Study on the method of thermal prediction for electronic wing pod cabin

Yang Chao
, Pang Liping
, Wang Jun
, Zhou Yue
, Qu Hongquan

航空科学与工程学院

Aero Electromechanical System Integration
North China University of Technology

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

2 引用（Scopus）

摘要

For airborne electronic equipment, temperature is the most important factor affecting its performance, so it is very important to invest its dynamic temperature response process in a flight environment. By analyzing the heat exchange relationship between different devices in an electronic wing pod cabin, a temperature prediction method for electronic pod cabin based on the Random Vector Functional Link (RVFL) neural network is proposed in this paper. This method can complete a construction of prediction model using small amount of data. Hence it can realize a quick temperature response prediction only with the initial temperature values, and ensure relative high prediction accuracy.

源语言	英语
主期刊名	Proceedings IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society
出版商	Institute of Electrical and Electronics Engineers Inc.
页	4183-4187
页数	5
ISBN（电子版）	9781538611272
DOI	https://doi.org/10.1109/IECON.2017.8216717
出版状态	已出版 - 15 12月 2017
活动	43rd Annual Conference of the IEEE Industrial Electronics Society, IECON 2017 - Beijing, 中国期限: 29 10月 2017 → 1 11月 2017

出版系列

姓名	Proceedings IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society
卷	2017-January

会议

会议	43rd Annual Conference of the IEEE Industrial Electronics Society, IECON 2017
国家/地区	中国
市	Beijing
时期	29/10/17 → 1/11/17

访问文件

10.1109/IECON.2017.8216717

其它文件与链接

链接到 Scopus 的出版物

引用此

Chao, Y., Liping, P., Jun, W., Yue, Z., & Hongquan, Q. (2017). Study on the method of thermal prediction for electronic wing pod cabin. 在 Proceedings IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society (页码 4183-4187). (Proceedings IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society; 卷 2017-January). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IECON.2017.8216717

Chao, Yang ; Liping, Pang ; Jun, Wang 等. / Study on the method of thermal prediction for electronic wing pod cabin. Proceedings IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society. Institute of Electrical and Electronics Engineers Inc., 2017. 页码 4183-4187 (Proceedings IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society).

@inproceedings{d30d6f867a5d40e0b2669c32ce10e2ad,

title = "Study on the method of thermal prediction for electronic wing pod cabin",

abstract = "For airborne electronic equipment, temperature is the most important factor affecting its performance, so it is very important to invest its dynamic temperature response process in a flight environment. By analyzing the heat exchange relationship between different devices in an electronic wing pod cabin, a temperature prediction method for electronic pod cabin based on the Random Vector Functional Link (RVFL) neural network is proposed in this paper. This method can complete a construction of prediction model using small amount of data. Hence it can realize a quick temperature response prediction only with the initial temperature values, and ensure relative high prediction accuracy.",

keywords = "electronic wing pod cabin, RVFL neural network, temperature prediction",

author = "Yang Chao and Pang Liping and Wang Jun and Zhou Yue and Qu Hongquan",

note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 43rd Annual Conference of the IEEE Industrial Electronics Society, IECON 2017 ; Conference date: 29-10-2017 Through 01-11-2017",

year = "2017",

month = dec,

day = "15",

doi = "10.1109/IECON.2017.8216717",

language = "英语",

series = "Proceedings IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society",

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

pages = "4183--4187",

booktitle = "Proceedings IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society",

address = "美国",

}

Chao, Y , Liping, P , Jun, W, Yue, Z & Hongquan, Q 2017, Study on the method of thermal prediction for electronic wing pod cabin. 在 Proceedings IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society. Proceedings IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society, 卷 2017-January, Institute of Electrical and Electronics Engineers Inc., 页码 4183-4187, 43rd Annual Conference of the IEEE Industrial Electronics Society, IECON 2017, Beijing, 中国, 29/10/17. https://doi.org/10.1109/IECON.2017.8216717

Study on the method of thermal prediction for electronic wing pod cabin. / Chao, Yang ; Liping, Pang ; Jun, Wang 等.
Proceedings IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society. Institute of Electrical and Electronics Engineers Inc., 2017. 页码 4183-4187 (Proceedings IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society; 卷 2017-January).

科研成果: 书/报告/会议事项章节 › 会议稿件 › 同行评审

TY - GEN

T1 - Study on the method of thermal prediction for electronic wing pod cabin

AU - Chao, Yang

AU - Liping, Pang

AU - Jun, Wang

AU - Yue, Zhou

AU - Hongquan, Qu

PY - 2017/12/15

Y1 - 2017/12/15

N2 - For airborne electronic equipment, temperature is the most important factor affecting its performance, so it is very important to invest its dynamic temperature response process in a flight environment. By analyzing the heat exchange relationship between different devices in an electronic wing pod cabin, a temperature prediction method for electronic pod cabin based on the Random Vector Functional Link (RVFL) neural network is proposed in this paper. This method can complete a construction of prediction model using small amount of data. Hence it can realize a quick temperature response prediction only with the initial temperature values, and ensure relative high prediction accuracy.

AB - For airborne electronic equipment, temperature is the most important factor affecting its performance, so it is very important to invest its dynamic temperature response process in a flight environment. By analyzing the heat exchange relationship between different devices in an electronic wing pod cabin, a temperature prediction method for electronic pod cabin based on the Random Vector Functional Link (RVFL) neural network is proposed in this paper. This method can complete a construction of prediction model using small amount of data. Hence it can realize a quick temperature response prediction only with the initial temperature values, and ensure relative high prediction accuracy.

KW - electronic wing pod cabin

KW - RVFL neural network

KW - temperature prediction

UR - https://www.scopus.com/pages/publications/85046660233

U2 - 10.1109/IECON.2017.8216717

DO - 10.1109/IECON.2017.8216717

M3 - 会议稿件

AN - SCOPUS:85046660233

T3 - Proceedings IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society

SP - 4183

EP - 4187

BT - Proceedings IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 43rd Annual Conference of the IEEE Industrial Electronics Society, IECON 2017

Y2 - 29 October 2017 through 1 November 2017

ER -

Chao Y , Liping P , Jun W, Yue Z, Hongquan Q. Study on the method of thermal prediction for electronic wing pod cabin. 在 Proceedings IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society. Institute of Electrical and Electronics Engineers Inc. 2017. 页码 4183-4187. (Proceedings IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society). doi: 10.1109/IECON.2017.8216717

Study on the method of thermal prediction for electronic wing pod cabin

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