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

School of Aeronautic Science and Engineering

Aero Electromechanical System Integration
North China University of Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Scopus citations

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.

Original language	English
Title of host publication	Proceedings IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	4183-4187
Number of pages	5
ISBN (Electronic)	9781538611272
DOIs	https://doi.org/10.1109/IECON.2017.8216717
State	Published - 15 Dec 2017
Event	43rd Annual Conference of the IEEE Industrial Electronics Society, IECON 2017 - Beijing, China Duration: 29 Oct 2017 → 1 Nov 2017

Publication series

Name	Proceedings IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society
Volume	2017-January

Conference

Conference	43rd Annual Conference of the IEEE Industrial Electronics Society, IECON 2017
Country/Territory	China
City	Beijing
Period	29/10/17 → 1/11/17

Keywords

electronic wing pod cabin
RVFL neural network
temperature prediction

Access to Document

10.1109/IECON.2017.8216717

Cite this

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

Chao, Yang ; Liping, Pang ; Jun, Wang et al. / 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. pp. 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. in Proceedings IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society. Proceedings IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society, vol. 2017-January, Institute of Electrical and Electronics Engineers Inc., pp. 4183-4187, 43rd Annual Conference of the IEEE Industrial Electronics Society, IECON 2017, Beijing, China, 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 et al.
Proceedings IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society. Institute of Electrical and Electronics Engineers Inc., 2017. p. 4183-4187 (Proceedings IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society; Vol. 2017-January).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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. In Proceedings IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society. Institute of Electrical and Electronics Engineers Inc. 2017. p. 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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