高压电器2025，Vol.61Issue(7)：8-15,8.DOI:10.13296/j.1001-1609.hva.2025.07.002
基于边缘智能的发电机定转子故障实时监测系统
Real-time Monitoring System for Generator Stator and Rotor Faults Based on Edge Intelligence
摘要
Abstract
Rotor extraction is an important work to be performed in the periodic overhaul of nuclear power units.However,excessive overhaul can lead to the damage risk of both stator and rotor and increase of operating cost.It is found by the research that the feasibility of stator and rotor defect detection in case of not extracting the rotor of the generator is of significance in reducing the maintenance costs.The tracked robot is used to detect the images collect-ed by four cameras in real-time through the edge computing equipment.Based on the YOLOv7 original network,the effects of various optimization methods on the network's generalization ability are investigated by using Mosaic-9 data augmentation and optimizing the Wise-IoU loss function.The results show that under the condition of con-stant recognition speed,the optimized YOLOv7 has superior performance metrics,faster detection speed,and fewer model parameters.Consequently,it is more suitable for deployment on the edge module.Furthermore,multiple on-site tests also show that the robot system is capable of detecting faults in the stator and rotor without the need for ro-tor extraction.关键词
边缘计算/深度神经网络/故障检测/不抽转子检测/工业机器人Key words
edge computing/deep neural networks/fault detection/generator in-situ inspection/industrial robots引用本文复制引用
陶子健,吴鹏,谢琮玖,秦亮亮,王军,房静,周凤领,谢庆..基于边缘智能的发电机定转子故障实时监测系统[J].高压电器,2025,61(7):8-15,8.基金项目
核电运行研究(上海)有限公司资助项目(KY-B-21-012).Project Supported by Nuclear Power Operations Research Institute Co.,Ltd.(KY-B-21-012). （上海）
