| Issue |
MATEC Web of Conf.
Volume 399, 2024
2024 3rd International Conference on Advanced Electronics, Electrical and Green Energy (AEEGE 2024)
|
|
|---|---|---|
| Article Number | 00010 | |
| Number of page(s) | 5 | |
| DOI | https://doi.org/10.1051/matecconf/202439900010 | |
| Published online | 24 June 2024 | |
Design and Development a Software for Wear Measurement of Control Rod Guide Card Based on Machine Vision
CGNPC Inspection Technology Co Ltd, Jiangsu, Suzhou, China
* Qianfei Yang, sensefree@126.com
The control rod guide tube (CRGT) is used to protect the rod cluster control assembly (RCCA) from bending while providing guidance for the up and down movement of the RCCA. This ensures that the dropping time of the RCCA meets nuclear safety requirements and stops nuclear reactions within the specified time frame. During the up and down movement of the RCCA, the control rod guide cards (CRGC) may experience axial and vibration wear. If the wear is severe, the CRGC may lose its guiding function, resulting in serious problems such as delayed dropping time. In this paper, a machine vision method is proposed to measure the dimensions of the CRGC. Edge extraction, image rectification, and template matching are used to realize autonomous measurement of the CRGC based on its features. The developed measurement software has been used 5 times in domestic nuclear power plant overhauls and has detected 15 CRGTs that were close to the wear limit. This provided data support for the replacement of the CRGTs and effectively improved the quality of nuclear power operation.
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.