Remote Visual Inspection (RVI) of reactors in nuclear power plants allows station operators to assess the health and condition of their plant. In the UK, most nuclear stations are of the Advanced Gas-cooled Reactor (AGR) design. During planned periodic outages, a representative portion of each AGR core is inspected using specialist tools equipped with various sensors including a video camera for RVI. If cracks are observed in the core during data capture, a stitched image of the region needs to be created so that the crack can be analysed and sentenced (classifying the crack morphology, location, orientation and size) before the station is returned to service, provided return to service is justified. Currently, the crack analysis and sizing activities are conducted manually by expert analysts in a laborious process. In this paper, we present a new image processing approach capable of automating aspects of the crack analysis process. Specifically, we describe a set of techniques for quickly and accurately detecting the presence of cracks in AGR fuel channel inspection images. We also present a method for detecting circular channel features known as trepanned holes whose dimensions are known and can thus be used for scaling. The results of applying the proposed techniques are evaluated on image data from real AGR fuel channels and are shown to produce comparable results to those obtained manually. The advantage of the proposed approach is that it is fast, robust and more repeatable than the existing manual approach.
- decision support systems
- nuclear power generation safety
- nuclear engineering
- nuclear power plant