Research on digital twin modeling technology for converter valves based on multi-physical quantity sensing

Rui Chen; Yanjie An; Zhiyuan Liu; Xinyang Zhao; Hongjian Lu; Haoyang Chen; Tianqi Li

doi:10.1117/12.2680833

23 May 2023 Research on digital twin modeling technology for converter valves based on multi-physical quantity sensing

Rui Chen, Yanjie An, Zhiyuan Liu, Xinyang Zhao, Hongjian Lu, Haoyang Chen, Tianqi Li

Author Affiliations +

Proceedings Volume 12645, International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2023); 126454Z (2023) https://doi.org/10.1117/12.2680833
Event: International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2023), 2023, Hangzhou, China

Abstract

The digital twin is one of the key technologies driving the digital transformation of power equipment, providing new opportunities for the construction of new power systems. As an important transmission and transformation equipment in the power system, high-voltage converter stations can be monitored by multi-physical quantity sensing technology to ensure reliable operation of the converter valves. The key issue is therefore how to obtain the operating state of the multi-physical quantities in the valve hall. To this end, this paper studies a three-dimensional twin model for the converter valve based on the advantages of the digital twin five-dimensional model and visualizes the operating temperature and pressure states in the valve hall through the sensor monitoring data, showing that the results are of some significance for the deployment of multi-physics sensors and the stable operation of the converter valve.

Citation Download Citation

Rui Chen, Yanjie An, Zhiyuan Liu, Xinyang Zhao, Hongjian Lu, Haoyang Chen, and Tianqi Li "Research on digital twin modeling technology for converter valves based on multi-physical quantity sensing", Proc. SPIE 12645, International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2023), 126454Z (23 May 2023); https://doi.org/10.1117/12.2680833

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

;

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE