Research on digital twin-based capacitive voltage transformer operating condition monitoring method

Ming Zhang; Xuan Yang; Zimu Wang; Lei Mao; Yini Zhao

doi:10.1117/12.2672771

16 March 2023 Research on digital twin-based capacitive voltage transformer operating condition monitoring method

Ming Zhang, Xuan Yang, Zimu Wang, Lei Mao, Yini Zhao

Proceedings Volume 12593, Second Guangdong-Hong Kong-Macao Greater Bay Area Artificial Intelligence and Big Data Forum (AIBDF 2022); 125931I (2023) https://doi.org/10.1117/12.2672771
Event: 2nd Guangdong-Hong Kong-Macao Greater Bay Area Artificial Intelligence and Big Data Forum (AIBDF 2022), 2022, Guangzhou, China

Abstract

The capacitive voltage transformer operating condition monitoring method has the problem of excessive error, in order to design a digital twin-based capacitive voltage transformer operating condition monitoring method. The capacitive voltage transformer transmission characteristics are identified, the harmonic measurement signal is obtained by using a series-connected voltage divider, an equivalent circuit model is constructed based on digital twin, the capacitive transformer fault gas data is extracted and uploaded to the digital twin database, and the operating condition monitoring method is designed. The results show that the mean error value of this designed capacitive voltage transformer operating condition monitoring method is 24.334%, indicating that the capacitive voltage transformer operating condition monitoring method in the paper is more effective after combining digital twin technology.

Citation Download Citation

Ming Zhang, Xuan Yang, Zimu Wang, Lei Mao, and Yini Zhao "Research on digital twin-based capacitive voltage transformer operating condition monitoring method", Proc. SPIE 12593, Second Guangdong-Hong Kong-Macao Greater Bay Area Artificial Intelligence and Big Data Forum (AIBDF 2022), 125931I (16 March 2023); https://doi.org/10.1117/12.2672771

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

Includes PDF, HTML & Video, when available