微型电脑应用2025，Vol.41Issue(3)：247-250,4.
基于迁移学习AlexNet的关键输电线路舞动形态特征辨识技术
Identification Technology of Galloping Morphological Features of Key Transmission Lines Based on Transfer Learning AlexNet
刘洋1
作者信息
- 1. 国网吉林省电力有限公司吉林供电公司,吉林,吉林 132001
- 折叠
摘要
Abstract
Aiming at the problems of large positioning error,large galloping intensity error and large monitoring position error in the breeze environment,a key transmission lines galloping shape features identification technology based on transfer learning AlexNet is proposed.The precise identification of galloping characteristics of key transmission lines is completed by combining GPS positioning and pseudo range difference method.The comparison test shows that the vibration curve of the proposed meth-od is consistent with the actual vibration position.The frequency corresponding to the peak value of the vibration intensity curve is the same as the vibration frequency set in the experiment.The obtained vibration position is closest to the actual vibra-tion position.The proposed method has small positioning error,small positioning galloping intensity error and small monitoring position error in breeze environment which is conducive to the identification of galloping morphological characteristics of key transmission lines.关键词
迁移学习/AlexNet神经网络/输电线路舞动/形态特征/辨识技术Key words
transfer learning/AlexNet neural network/transmission lines galloping/morphological feature/identification tech-nology分类
信息技术与安全科学引用本文复制引用
刘洋..基于迁移学习AlexNet的关键输电线路舞动形态特征辨识技术[J].微型电脑应用,2025,41(3):247-250,4.
