Currently,the inspection of substation protection hard platens is mostly carried out manual-ly,involving time-consuming and error-prone tasks,which does not meet the requirements for intelligent secondary equipment in substations.This paper presents a study on the detection and state recognition technology of substation protection hard platens based on the YOLOv3 algorithm.Firstly,a dataset contai-ning large samples is established through data collection and annotation of substation protection hard plat-ens.Then,the YOLOv3 algorithm is employed for object detection,achieving accurate localization and rec-ognition of the substation protection hard platens.Different feature extraction and classification modules are designed for different states of the hard platens,enabling accurate state recognition of the detected plat-ens.Experimental results demonstrate that this method exhibits high accuracy.This paper provides valuable in-sights for implementing tasks such as the confirmation of platen operation tickets and platen status verification,of-fering effective technical support for substation equipment intelligent monitoring and fault diagnosis.
关键词
变电站/二次保护/YOLOv3算法/压板状态识别
Key words
substation/secondary protection/YOLOv3 algorithm/platen state recognition
维普
万方数据