Research on Machine Vision Measurement Method of Rod Spacing Data for PWR Fuel after Irradiation

Li Weicai; Liu Pengliang; Wang Congzheng; Guo Yan

doi:10.13832/j.jnpe.2022.04.0053

Volume 43 Issue 4

Aug. 2022

Turn off MathJax

Article Contents

Article Navigation > Nuclear Power Engineering > 2022 > 43(4): 53-59

Li Weicai, Liu Pengliang, Wang Congzheng, Guo Yan. Research on Machine Vision Measurement Method of Rod Spacing Data for PWR Fuel after Irradiation[J]. Nuclear Power Engineering, 2022, 43(4): 53-59. doi: 10.13832/j.jnpe.2022.04.0053

Citation:

Li Weicai, Liu Pengliang, Wang Congzheng, Guo Yan. Research on Machine Vision Measurement Method of Rod Spacing Data for PWR Fuel after Irradiation[J]. Nuclear Power Engineering, 2022, 43(4): 53-59. doi: 10.13832/j.jnpe.2022.04.0053

Citation:

PDF( 18852 KB)

Research on Machine Vision Measurement Method of Rod Spacing Data for PWR Fuel after Irradiation

doi: 10.13832/j.jnpe.2022.04.0053

1.
China Nuclear Power Technology Research Institute, Shenzhen, Guangdong, 518031, China
2.
Institute of Optics and Electronics, Chinese Academy of Science, Chengdu, 610209, China

Received Date: 2021-07-06
Accepted Date: 2022-01-26
Rev Recd Date: 2021-09-24

Available Online: 2022-08-11

Publish Date: 2022-08-04

Abstract

Abstract

To address the difficulty of obtaining and processing fuel rod spacing data after irradiation, based on the geometric characteristics of fuel rods and their arrangement in PWR fuel assemblies, this paper proposes an efficient and reliable method for measuring fuel rod spacing data based on machine vision. The method first uses Retinex algorithm to enhance the preprocessing of the collected images of underwater fuel rods; then, for the front and rear imaging interference problem of the fuel rod array, edge enhancement and line-by-line grayscale feature processing methods are used to effectively separate the fuel rods to be tested from the background fuel rods, and further improve the image clarity; finally, the single-row gray value of the fuel rod image is fitted with quadratic curve to obtain the sub-pixel edge point coordinates of each fuel rod. The field experimental verification results of spent fuel assemblies show that this method can realize the rod spacing measurement of 16 fuel rods at one time, and the measurement accuracy is up to ±0.32 mm, which can provide efficient and reliable data support for fuel performance analysis.
- Pressurized water reactor (PWR),
- Fuel rod,
- Rod spacing,
- Machine vision measurement

FullText(HTML)

References(19)

References

[1]	DENG J X, DENG F. The setting of sipping test devices for irradiated fuel in nuclear power plant[J]. Journal of Energy and Power Engineering, 2002, 6(12): 1935-1939.
[2]	任亮,李国云,江林志,等. 压水堆燃料组件池边检查技术研究进展[J]. 科技导报,2015, 33(18): 91-95. doi: 10.3981/j.issn.1000-7857.2015.18.015
[3]	刘晓松. 破损燃料组件热室检查技术研究[J]. 核动力工程,2018, 39(4): 71-74.
[4]	王从政. 基于水下耐辐照相机的燃料组件变形双目检测系统研究[D]. 成都: 电子科技大学, 2018: 4-9.
[5]	王雄,杜代全,曾小康,等. VVER反应堆燃料组件流动传热特性CFD分析[J]. 核动力工程,2018, 39(3): 6-9.
[6]	殷振国,王华才,刘歆粤,等. 燃料棒破损超声检测技术研究[J]. 原子能科学与技术,2015, 49(2): 324-329.
[7]	DUJON G F, PARKER A B, THOMAS A J. Visual image transmission by fibre optic cable: US, 5327514[P]. 1994-07-05.
[8]	刘敬露,韩震宇. 核燃料组件变形测量系统的研制[J]. 计量与测试技术,2005, 32(11): 10-11,13. doi: 10.3969/j.issn.1004-6941.2005.11.004
[9]	李建伟,何高魁,张向阳,等. 高能X射线CT技术在辐照后核燃料组件检测中的发展及应用[J]. 同位素,2020, 33(2): 124-132. doi: 10.7538/tws.2018.youxian.100
[10]	李强,任宇宏,邹树梁,等. 基于LabVIEW的核燃料组件图像倾斜处理技术研究[J]. 机械工程与自动化,2019(1): 24-26+30. doi: 10.3969/j.issn.1672-6413.2019.01.009
[11]	王从政,胡松,高椿明,等. 水下热扰动的光学成像失真问题研究[J]. 光电工程,2019, 46(10): 1-9.
[12]	程曦,周国正,唐西明,等. 基于涡流技术的燃料棒氧化膜测量信号有效性评估与统计[J]. 核动力工程,2020, 41(1): 49-53.
[13]	邹立,卢俊彦,胡易,等. 非均匀光照条件下的水下图像增强算法[J]. 山东科技大学学报(自然科学版),2020, 39(2): 118-125.
[14]	林明星,代成刚,董雪,等. 水下图像处理技术研究综述[J]. 测控技术,2020, 39(8): 7-20.
[15]	LAND E H, MCCANN J J. Lightness and retinex theory[J]. Journal of the Optical Society of America, 1971, 61(1): 1-11. doi: 10.1364/JOSA.61.000001
[16]	谢美华,王正明. 基于边缘定向增强的各向异性扩散抑噪方法[J]. 电子学报,2006, 34(1): 59-64. doi: 10.3321/j.issn:0372-2112.2006.01.012
[17]	董鸿燕. 边缘检测的若干技术研究[D]. 长沙: 国防科学技术大学, 2008: 14-16.
[18]	GONZALEZ R C, WOODS R E. 数字图像处理[M]. 阮秋琦, 阮宇智, 译. 北京: 电子工业出版社, 2003: 87-92.
[19]	WU Z R, ROBINSON J. Edge-preserving colour-to-greyscale conversion[J]. IET Image Processing, 2014, 8(4): 252-260. doi: 10.1049/iet-ipr.2013.0348