Implementation of surface crack detection method for nuclear fuel pellets guided by convolution neural network-Reference-Cited by-同舟云学术

Implementation of surface crack detection method for nuclear fuel pellets guided by convolution neural network

Published:2021-01-04 Issue:7 Volume:58 Page:787-796
ISSN:0022-3131
Container-title:Journal of Nuclear Science and Technology
language:en
Short-container-title:Journal of Nuclear Science and Technology

Author:

Zhang Bin¹^ORCID,Miao Yanjie¹^ORCID,Tian Yongzhi¹,Zhang Wenjie¹,Wu Ge¹,Wang Xinmiao¹,Zhang Chaoying¹

Affiliation:

1. School of Physics and Microelectronics, Zhengzhou University, Zhengzhou, China

Funder

The pellet appearance automatic inspection device visual system

Publisher

Informa UK Limited

Subject

Nuclear Energy and Engineering,Nuclear and High Energy Physics

Link

https://www.tandfonline.com/doi/pdf/10.1080/00223131.2020.1869622

Reference24 articles.

1. Piro MHA, Sunderland D, Livingstone S, et al.A review of pellet–clad interaction behavior in Zirconium alloy fuel cladding. In: YilbasB. (Ed.). Reference module in materials science and materials engineering. Amsterdam: Elsevier; 2017. p. 1–68

2. Yang DG Study on MOX fuel pellets sintering process and device. Harbin: Harbin Engineering University, 2016.

3. Joshi M, Deshpande P, Navathe CP. Development of image processing and analyzing software for nuclear fuel pellet end faces. APCNDT-2013. 2014; Indore, India.

4. Automatic defect identification on PWR nuclear power station fuel pellets

5. High Productive Optoelectronic Pellets Surface Inspection for Nuclear Reactors

Cited by 11 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Damage detection and localization in sealed spent nuclear fuel dry storage canisters using multi-task machine learning classifiers;Reliability Engineering & System Safety;2024-12

2. Implementation of surface crack detection method for nuclear fuel pellets by weakly supervised learning;Journal of Nuclear Science and Technology;2024-07-07

3. Machine learning-aided damage identification of mock-up spent nuclear fuel assemblies in a sealed dry storage canister;Engineering Applications of Artificial Intelligence;2024-02

4. Designing an event management system for campus football using 3D images and machine vision;Signal, Image and Video Processing;2024-01-14

5. Integrating DeblurGAN and CNN to improve the accuracy of motion blur X-Ray image classification;Journal of Nuclear Science and Technology;2023-07-20