Optimization study of a clustering algorithm for cosmic-ray muon scattering tomography used in fast inspection

Autor: Linjun Hou, Yonggang Huo, Wenming Zuo, Qingxu Yao, Jianqing Yang, Quanhu Zhang
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: Nuclear Engineering and Technology, Vol 53, Iss 1, Pp 208-215 (2021)
Druh dokumentu: article
ISSN: 1738-5733
DOI: 10.1016/j.net.2020.06.004
Popis: Cosmic-ray muon scattering tomography (MST) technology is a new radiation imaging technology with unique advantages. As the performance of its image reconstruction algorithm has a crucial influence on the imaging quality, researches on this algorithm are of great significance to the development and application of this technology. In this paper, a fast inspection algorithm based on clustering analysis for the identification of the existence of nuclear materials is studied and optimized. Firstly, the principles of MST technology and a binned clustering algorithm were introduced, and then several simulation experiments were carried out using Geant4 toolkit to test the effects of exposure time, algorithm parameter, the size and structure of object on the performance of the algorithm. Based on these, we proposed two optimization methods for the clustering algorithm: the optimization of vertical distance coefficient and the displacement of sub-volumes. Finally, several sets of experiments were designed to validate the optimization effect, and the results showed that these two optimization methods could significantly enhance the distinguishing ability of the algorithm for different materials, help to obtain more details in practical applications, and was therefore of great importance to the development and application of the MST technology.
Databáze: Directory of Open Access Journals