Abstract:
This article addresses the high-efficiency and high-precision requirements for quality inspection of nuclear fuel rod welds. It designs and implements an online automated evaluation system. The system adopts a B/S architecture and integrates advanced AI technology to achieve real-time image acquisition, management, and intelligent analysis of fuel rod welds. The front end of the system utilizes Electron.js, React, and Ant Design frameworks, while the back end is based on Spring Cloud and Docker technologies, ensuring ease of operation and system stability. Through integrated AI models, the system effectively identifies weld defects, enhancing inspection accuracy and production efficiency. The successful implementation of this system provides robust support for the safe operation of nuclear power plants and quality control in the nuclear energy industry, laying the foundation for future developments in automated inspection technology.