Research on online monitoring device of capacitive voltage transformer based on deep learning

Zhuorun Li; Guolong Zhen; Yazhou Zhang; Jin Wang

doi:10.1117/12.3037951

12 September 2024 Research on online monitoring device of capacitive voltage transformer based on deep learning

Zhuorun Li, Guolong Zhen, Yazhou Zhang, Jin Wang

Proceedings Volume 13256, Fourth International Conference on Computer Vision and Pattern Analysis (ICCPA 2024); 1325621 (2024) https://doi.org/10.1117/12.3037951
Event: Fourth International Conference on Computer Vision and Pattern Analysis (ICCPA 2024), 2024, Anshan, China

Abstract

The capacitor voltage transformer (CVT) is a measuring device that converts high voltage into a low voltage signal. It is better than the electromagnetic voltage transformer (PT) in terms of economy and protection against interference, so it is widely used in stations and substations of 35kV and above. Currently, CVT are still mainly inspected by the shutdown inspection method on a four-year cycle, which cannot meet the demand for intelligent monitoring of key equipment in smart substations. Considering the above problems, this paper investigates a device based on the deep learning prediction algorithm to realize intelligent in-line CVT prediction, which has good performance in terms of functionality and reliability.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Zhuorun Li, Guolong Zhen, Yazhou Zhang, and Jin Wang "Research on online monitoring device of capacitive voltage transformer based on deep learning", Proc. SPIE 13256, Fourth International Conference on Computer Vision and Pattern Analysis (ICCPA 2024), 1325621 (12 September 2024); https://doi.org/10.1117/12.3037951

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