Research on Health Monitoring and Intelligent Diagnosis Technology of Large-Scale Low-Speed Wind Tunnel

Wang Jianfeng; Liu Boya; Liu Shi

doi:10.1007/978-981-19-7652-0_47

Research on Health Monitoring and Intelligent Diagnosis Technology of Large-Scale Low-Speed Wind Tunnel

Wang Jianfeng
, Liu Boya^*
, Liu Shi

^*Corresponding author for this work

AVIC Aerodynamics Research Institute
Aviation Key Laboratory of Aerodynamics for Low Speed & High Renolds Number

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

1 Scopus citations

Abstract

The large-scale low-speed wind tunnel test system is complex, involving many equipment, parameters, and data. In order to monitor the state of the system, quickly determine and locate the cause of the fault when the system is abnormal. Based on advanced sensors and network technology, this paper monitors the components and parameters of the system in real time. Through the three-dimensional simulation method, the digital twin system construction of the wind tunnel system including the model is realized, and the data visualization method is combined with the machine learning technology to intelligently predict and diagnose the faults and causes of the test data. Through the research in this paper, the technical foundation is laid for the construction of the smart wind tunnel laboratory.

Original language	English
Title of host publication	Proceedings of the 10th Chinese Society of Aeronautics and Astronautics Youth Forum
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	518-536
Number of pages	19
ISBN (Print)	9789811976513
DOIs	https://doi.org/10.1007/978-981-19-7652-0_47
State	Published - 2023
Externally published	Yes
Event	10th Chinese Society of Aeronautics and Astronautics Youth Forum, 2022 - Nanchang, China Duration: 9 Oct 2022 → 10 Oct 2022

Publication series

Name	Lecture Notes in Electrical Engineering
Volume	972 LNEE
ISSN (Print)	1876-1100
ISSN (Electronic)	1876-1119

Conference

Conference	10th Chinese Society of Aeronautics and Astronautics Youth Forum, 2022
Country/Territory	China
City	Nanchang
Period	9/10/22 → 10/10/22

Keywords

Artificial intelligence
Deep learning
Digital twin
Fault diagnosis
Low-speed wind tunnel health monitoring

Access to Document

10.1007/978-981-19-7652-0_47

Cite this

Jianfeng, W., Boya, L., & Shi, L. (2023). Research on Health Monitoring and Intelligent Diagnosis Technology of Large-Scale Low-Speed Wind Tunnel. In Proceedings of the 10th Chinese Society of Aeronautics and Astronautics Youth Forum (pp. 518-536). (Lecture Notes in Electrical Engineering; Vol. 972 LNEE). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-981-19-7652-0_47

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title = "Research on Health Monitoring and Intelligent Diagnosis Technology of Large-Scale Low-Speed Wind Tunnel",

abstract = "The large-scale low-speed wind tunnel test system is complex, involving many equipment, parameters, and data. In order to monitor the state of the system, quickly determine and locate the cause of the fault when the system is abnormal. Based on advanced sensors and network technology, this paper monitors the components and parameters of the system in real time. Through the three-dimensional simulation method, the digital twin system construction of the wind tunnel system including the model is realized, and the data visualization method is combined with the machine learning technology to intelligently predict and diagnose the faults and causes of the test data. Through the research in this paper, the technical foundation is laid for the construction of the smart wind tunnel laboratory.",

keywords = "Artificial intelligence, Deep learning, Digital twin, Fault diagnosis, Low-speed wind tunnel health monitoring",

author = "Wang Jianfeng and Liu Boya and Liu Shi",

note = "Publisher Copyright: {\textcopyright} 2023, Chinese Aeronautical Society.; 10th Chinese Society of Aeronautics and Astronautics Youth Forum, 2022 ; Conference date: 09-10-2022 Through 10-10-2022",

year = "2023",

doi = "10.1007/978-981-19-7652-0\_47",

language = "英语",

isbn = "9789811976513",

series = "Lecture Notes in Electrical Engineering",

publisher = "Springer Science and Business Media Deutschland GmbH",

pages = "518--536",

booktitle = "Proceedings of the 10th Chinese Society of Aeronautics and Astronautics Youth Forum",

address = "德国",

}

Jianfeng, W, Boya, L & Shi, L 2023, Research on Health Monitoring and Intelligent Diagnosis Technology of Large-Scale Low-Speed Wind Tunnel. in Proceedings of the 10th Chinese Society of Aeronautics and Astronautics Youth Forum. Lecture Notes in Electrical Engineering, vol. 972 LNEE, Springer Science and Business Media Deutschland GmbH, pp. 518-536, 10th Chinese Society of Aeronautics and Astronautics Youth Forum, 2022, Nanchang, China, 9/10/22. https://doi.org/10.1007/978-981-19-7652-0_47

Research on Health Monitoring and Intelligent Diagnosis Technology of Large-Scale Low-Speed Wind Tunnel. / Jianfeng, Wang; Boya, Liu; Shi, Liu.
Proceedings of the 10th Chinese Society of Aeronautics and Astronautics Youth Forum. Springer Science and Business Media Deutschland GmbH, 2023. p. 518-536 (Lecture Notes in Electrical Engineering; Vol. 972 LNEE).

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

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AU - Boya, Liu

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PY - 2023

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N2 - The large-scale low-speed wind tunnel test system is complex, involving many equipment, parameters, and data. In order to monitor the state of the system, quickly determine and locate the cause of the fault when the system is abnormal. Based on advanced sensors and network technology, this paper monitors the components and parameters of the system in real time. Through the three-dimensional simulation method, the digital twin system construction of the wind tunnel system including the model is realized, and the data visualization method is combined with the machine learning technology to intelligently predict and diagnose the faults and causes of the test data. Through the research in this paper, the technical foundation is laid for the construction of the smart wind tunnel laboratory.

AB - The large-scale low-speed wind tunnel test system is complex, involving many equipment, parameters, and data. In order to monitor the state of the system, quickly determine and locate the cause of the fault when the system is abnormal. Based on advanced sensors and network technology, this paper monitors the components and parameters of the system in real time. Through the three-dimensional simulation method, the digital twin system construction of the wind tunnel system including the model is realized, and the data visualization method is combined with the machine learning technology to intelligently predict and diagnose the faults and causes of the test data. Through the research in this paper, the technical foundation is laid for the construction of the smart wind tunnel laboratory.

KW - Artificial intelligence

KW - Deep learning

KW - Digital twin

KW - Fault diagnosis

KW - Low-speed wind tunnel health monitoring

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Y2 - 9 October 2022 through 10 October 2022

ER -

Research on Health Monitoring and Intelligent Diagnosis Technology of Large-Scale Low-Speed Wind Tunnel

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