Research on Automatic Calibration Algorithm of Reactor Fuel Rods

Li Xiangdong; Jiang Hesong; Wang Xueyuan; Xu Xuejin; He Xiaochun

doi:10.13832/j.jnpe.2023.04.0203

Volume 44 Issue 4

Aug. 2023

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Li Xiangdong, Jiang Hesong, Wang Xueyuan, Xu Xuejin, He Xiaochun. Research on Automatic Calibration Algorithm of Reactor Fuel Rods[J]. Nuclear Power Engineering, 2023, 44(4): 203-208. doi: 10.13832/j.jnpe.2023.04.0203

Citation:

Li Xiangdong, Jiang Hesong, Wang Xueyuan, Xu Xuejin, He Xiaochun. Research on Automatic Calibration Algorithm of Reactor Fuel Rods[J]. Nuclear Power Engineering, 2023, 44(4): 203-208. doi: 10.13832/j.jnpe.2023.04.0203

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Research on Automatic Calibration Algorithm of Reactor Fuel Rods

doi: 10.13832/j.jnpe.2023.04.0203

Li Xiangdong^1
,,
Jiang Hesong^{1, 2},
Wang Xueyuan^{1, 2
,
,},
Xu Xuejin¹,
He Xiaochun³

1.
School of Information Engineering, Southwest University of Science and Technology, Mianyang, Sichuan, 621000, China
2.
Robot Technology Used for Special Environment Key Laboratory of Sichuan Province, Mianyang, Sichuan, 621000, China
3.
Sichuan Jiuzhou Aerocont Technologies Co., Ltd., Mianyang, Sichuan, 621000, China

Received Date: 2022-09-02
Rev Recd Date: 2023-04-29
Publish Date: 2023-08-15

Abstract

Abstract

Since the nuclear reactors need frequent replacement of fuel rods, it is necessary to determine the type and installation position of the core fuel rods accurately to ensure the safe operation of the reactor. Herein, the global and local virtual two-dimensional coordinate mapping models have been established in terms of the distribution relationship of fuel rod installation positions. The local sequence pictures of each viewpoint are taken to identify the central position of the fuel rods in the local pictures, and the local virtual two-dimensional coordinate mapping model is calibrated. Then, the Euclidean distance between the central position of the fuel rods and the position in the calibrated local mapping model is measured to realize type refactor, and the core panoramic mosaic is further obtained to assist calibration. The simulation results show that the algorithm can effectively detect the type and installation position of fuel rods, the recognition rate is higher than 98%, the accuracy rate reaches 100%, and the panoramic mosaic results are stable and reliable. It has great application potential in the calibration of core fuel rods.
- Fuel rods,
- Multi-view,
- Feature matching,
- Registration,
- Deep learning

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References(16)

References

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