绕丝燃料棒自动外观缺陷检测系统设计

Design of an Automatic Appearance Defect Detection System for Wire Wound Fuel Rods

绕丝燃料棒是核反应堆中燃料组件的核心部件,燃料棒外径绕丝是燃料棒制造的关键工序,其外观质量是燃料组件十分关键的质量特性。本文以视频图像为切入点,机器视觉为技术支撑,借助深度学习建立绕丝燃料棒外观缺陷智能判别及自动定位方法。针对燃料棒表面缺陷特征,搭建高精度的图像采集系统,获取便于识别的燃料棒外观图像信息,研究检测算法能准确识别焊缝氧化色、划伤、异物、焊缝成形不良等缺陷,实现绕丝燃料棒外观缺陷的自动化检测。

Wire wound fuel rods are the core components of fuel assemblies in nuclear reactors.Wire wound outer diameter of fuel rods is a key process in fuel rod manufacturing,and their appearance quality is a crucial quality characteristic of fuel assemblies.This article takes video images as the starting point,machine vision as the technical support,and uses deep learning to establish an intelligent identification and automatic positioning method for the appearance defects of wire wound fuel rods.Based on the surface defect characteristics of fuel rods,a high-precision image acquisition system is built to obtain easily recognizable image information of fuel rod appearance.Research on detection algorithms can accurately identify defects such as weld oxidation color,scratches,foreign objects,and poor weld formation,achieving automated detection of appearance defects of wire wound fuel rods.