Intelligent Judgment of Wrong Wiring Method in Large-Scale Training of Electrical Testing

JiaHeng Xu, WeiWei Yang, Na Song, Wei Ren, Xiao Rong

2022

Abstract

In the paper, in view of the complex wiring in the large-scale training process of electrical testing, the trainer needs to frequently judge the wiring right and wrong status quo, and proposes an intelligent judgment method based on the YOLO algorithm, through the logical binding of the digitized equipment terminals and the connected wire relationship in the test, relying on the learning of standard wiring, the automatic identification of the test connection line is realized, which greatly saves labor costs, reduces the possibility of human error, and improves work efficiency. New ideas have been developed for the training of new employees to conduct large-scale voltage transformer error tests.

Paper Citation

in Harvard Style

Xu J., Yang W., Song N., Ren W. and Rong X. (2022). Intelligent Judgment of Wrong Wiring Method in Large-Scale Training of Electrical Testing. In Proceedings of the 2nd International Conference on New Media Development and Modernized Education - Volume 1: NMDME; ISBN 978-989-758-630-9, SciTePress, pages 229-234. DOI: 10.5220/0011909500003613

in Bibtex Style

@conference{nmdme22,
author={JiaHeng Xu and WeiWei Yang and Na Song and Wei Ren and Xiao Rong},
title={Intelligent Judgment of Wrong Wiring Method in Large-Scale Training of Electrical Testing},
booktitle={Proceedings of the 2nd International Conference on New Media Development and Modernized Education - Volume 1: NMDME},
year={2022},
pages={229-234},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011909500003613},
isbn={978-989-758-630-9},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 2nd International Conference on New Media Development and Modernized Education - Volume 1: NMDME
TI - Intelligent Judgment of Wrong Wiring Method in Large-Scale Training of Electrical Testing
SN - 978-989-758-630-9
AU - Xu J.
AU - Yang W.
AU - Song N.
AU - Ren W.
AU - Rong X.
PY - 2022
SP - 229
EP - 234
DO - 10.5220/0011909500003613
PB - SciTePress