This paper presents a special container scanner in which the radiation source is a conventional radiography 60 Co projector of (100 300)×3 7×10 10 Bq. With a special sensitive array detector, ...This paper presents a special container scanner in which the radiation source is a conventional radiography 60 Co projector of (100 300)×3 7×10 10 Bq. With a special sensitive array detector, invented by Institute of Nuclear Energy Technology (INET) of Tsinghua University and other technical innovations, the characteristics of the 60 Co scanner qualify it for use in container inspection. Its contrast indicator (CI) and image quality indicator (IQI) for 100 mm steel are equal to 0 7% and 2 5%, respectively, and the steel penetration (SP) is about 240 mm. The 60 Co container scanner is much more economical and more reliable than those scanners using an accelerator source. Also, its penetration ability is much better than that of an X ray machine scanner. This paper presents the system design, the main difficulties and their technical solutions, the inspection characteristics and the special features of the 60 Co scanner.展开更多
Introduction Muon scattering tomography(MST)can be employed to scan cargo containers and vehicles for special nuclear materials by using cosmic muons.However,the flux of cosmic ray muons is relatively low for direct d...Introduction Muon scattering tomography(MST)can be employed to scan cargo containers and vehicles for special nuclear materials by using cosmic muons.However,the flux of cosmic ray muons is relatively low for direct detection.Thus,the detection has to be done in a short timescale with small numbers of muons to satisfy the demands of practical applications.Method In this paper,we propose an artificial neural network(ANN)algorithm for material discrimination using MST.The muon scattering angles were simulated using Geant4 to formulate the training set,and the muon scatter angles were measured by Micromegas detection system to create the test set.Results The ANN-based algorithm presented here ensures a discrimination accuracy of 98.0%between aluminum,copper and tungsten in a 5 min measurement of 4×4×4 cm^(3)blocks.展开更多
文摘This paper presents a special container scanner in which the radiation source is a conventional radiography 60 Co projector of (100 300)×3 7×10 10 Bq. With a special sensitive array detector, invented by Institute of Nuclear Energy Technology (INET) of Tsinghua University and other technical innovations, the characteristics of the 60 Co scanner qualify it for use in container inspection. Its contrast indicator (CI) and image quality indicator (IQI) for 100 mm steel are equal to 0 7% and 2 5%, respectively, and the steel penetration (SP) is about 240 mm. The 60 Co container scanner is much more economical and more reliable than those scanners using an accelerator source. Also, its penetration ability is much better than that of an X ray machine scanner. This paper presents the system design, the main difficulties and their technical solutions, the inspection characteristics and the special features of the 60 Co scanner.
基金supported by the Program of National Natural Science Foundation of China Grant Nos.11805168 and 21805251
文摘Introduction Muon scattering tomography(MST)can be employed to scan cargo containers and vehicles for special nuclear materials by using cosmic muons.However,the flux of cosmic ray muons is relatively low for direct detection.Thus,the detection has to be done in a short timescale with small numbers of muons to satisfy the demands of practical applications.Method In this paper,we propose an artificial neural network(ANN)algorithm for material discrimination using MST.The muon scattering angles were simulated using Geant4 to formulate the training set,and the muon scatter angles were measured by Micromegas detection system to create the test set.Results The ANN-based algorithm presented here ensures a discrimination accuracy of 98.0%between aluminum,copper and tungsten in a 5 min measurement of 4×4×4 cm^(3)blocks.
