Advanced video analysis for automated feature identification on Special Nuclear Materials (SNM) packages

塞拉菲尔德有限公司负责特殊核材料(SNM)的储存，这些材料是塞拉菲尔德核电站60年来后处理活动的遗产。为了确保SNM包裹在Sellafield门店内的持续储存安全，有必要密切监控包裹在其存储位置(就地)时的外表面。这项研究的目的是开发新的图像和视频处理算法，可用于分析现有和未来的SNM检查视频，以自动检测和量化每个接受检查的SNM包的状况。具体地说，将设计技术来检测和量化SNM包装的以下特征：-任何凹痕、划痕或磨损的尺寸-破裂的证据-原始制造缺陷-腐蚀/颜色变化的证据如果成功，则将设计新的方法对所有SNM容器进行批量分析以进行检查，目的是确定需要进行异地检查和可能需要某种形式的再加工和/或重新包装的最低风险。还将评估特征检测算法的可解释性，目的是设计基于人工智能的可解释性解决方案。

Sellafield Ltd is responsible for the storage of Special Nuclear Materials (SNM) that are a legacy of 60 years of reprocessing activities on the Sellafield site. To provide confidence that SNM packages remain safe for continued storage within Sellafield's stores, it is necessary to closely monitor the exterior surface of the packages whilst they are in their storage location (in-situ). Such monitoring will inform the selection of packages for ex-situ inspection.The aim of this research is to develop new image and video processing algorithms which can be used to analyse existing and future SNM inspection videos to automatically detect and quantify the condition of each SNM package that undergoes inspection. Specifically, techniques will be designed to detect and quantify the following characteristics of SNM packages:-Dimensions of any dents, scratches or scuffs-Evidence of cracking-Original manufacturing defects-Evidence of corrosion/colour changeIf successful, new methods will then be designed to perform batch analysis of all SNM containers to undergo inspection with the aim of identifying those at most and least risk of requiring ex-situ inspection and, possibly, some form of re-processing and/or re-packaging. The explicability of the feature detection algorithms will also be assessed with the aim of designing explicable AI based solutions.