Digital twin development through auto-linking to manage legacy assets in nuclear power plants.

Digitalization of Nuclear Power Plants (NPPs) is critical for their safe and effective operation and maintenance. Development of Digital Twins (DTs) of NPP legacy assets and subsystems is key to achieving this goal. Doing this effectively requires a framework for intelligent allocation of limited resources. This framework is developed here by synthesizing emerging best practices with NPP operators' needs for legacy assets management. Within the framework, a pipeline employs deep-learning object detection to read and locate equipment tags in images. It computes their locations in the corresponding 3D point clouds and then relates that data to an asset management system. The pipeline is premised on preservation and augmentation of existing NPP asset management processes that preclude options such as RFID tags or barcodes. It is a significant step toward more efficient development of DTs of legacy assets. The contributions are framed in the context of a typical Canadian legacy NPP. • A framework that defines the key aspects of legacy assets for Digital Twins. • Automatic link between photographic records and asset management software. • Performance of tag detection and optical character recognition on real images. • Pipeline for efficient linking of assets in point clouds to management systems. • Identification of asset locations using legacy asset tags in nuclear power plants. [ABSTRACT FROM AUTHOR]