The use of muon scattering tomography for the non-invasive characterisation of nuclear waste is well established. We report here on the application of a combination of feature discriminators and multivariate analysis techniques to locate and identify materials in nuclear waste drums. After successful training and optimisation of the algorithms they are then tested on a range of material configurations to assess the system's performance and limitations. The system is able to correctly identify uranium, iron and lead objects on a few cm scale. The system's sensitivity to small uranium objects is also established as 0.90^+0.07 _-0.12, with a false positive rate of 0.12^+0.12 _-0.07.

使用μ子散射断层扫描对核废料进行非侵入性表征已经很成熟。我们在此报告结合使用特征鉴别器和多变量分析技术来定位和识别核废料桶中的材料。在成功训练和优化算法后，他们将在一系列材料配置上进行测试，以评估系统的性能和局限性。该系统能够正确识别几厘米尺度上的铀、铁和铅物体。系统对小铀物体的敏感度也确定为0.90 ^+0.07 _-0.12，误报率为0.12 ^+0.12 _-0.07。