Improved Visual Inspection of Advanced Gas-Cooled Reactor Fuel Channels



Published Nov 3, 2020
Graeme West Paul Murray Stephen Marshall Stephen McArthur


Visual inspection of fuel channels is important for assessing the health of the UK’s fleet of Advanced Gas-Cooled Reactor (AGR) power plants. For each fuel channel inspected, any defects found must be classified and assessed by a panel of experts and documented before the plant can return to service. Part of the current inspection process involves extracting relevant frames from visual inspection videos and manually assembling them to form a “crack montage” image. As the plants age, there is increasing pressure to inspect more fuel channels. Dealing with this increase in inspection demand requires new techniques to support the analysis of an increased volume of gathered video data so that crack montages can be made within the tight timescales of the outages. Recent work by the authors has created a technique for automatically processing inspection videos to extract the relevant frames and produce so called chanoramas from which any required defect montages can be cropped. Chanoramas are 360° panoramic images, which show the entire inside surface of the fuel channel inspected, and this provides completely a new way for plant operators to view their visual inspection data and analyse the condition of AGR fuel channels. In this paper we present an industrial case study which first introduces the concept of a chanorama and summarises some initial findings of testing the techniques used to create them. Then, based on the initial testing results, new and advanced image processing techniques which have been designed to improve the quality of the final chanoramas are presented. The paper then expands upon the use of the raw data and describes techniques for rendering it to allow 3D visualisations of the fuel channels which allow inspection engineers to view features of interest from a range of different angles.

Abstract 158 | PDF Downloads 187



condition monitoring, visual inspection, image processing, Lifetime Extension

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