基于改进YOLOv7-Tiny技术的变电设备红外图像识别系统
Infrared Image Recognition System for Substation Equipment Based on Improved YOLOv7-Tiny Technology
宋金珠 1石超 1王炎2
作者信息
- 1. 国网河南省电力公司超高压公司,河南 郑州 450000
- 2. 国网河南省电力公司直流中心,河南 郑州 450000
- 折叠
摘要
原始YOLOv7-Tiny在处理变电设备红外图像时会面临识别精度不足和处理速度较慢的问题.为了解决这些问题,引入了一种新的模型调整策略,并对比了改进前后算法在标准红外图像数据集上的表现.结果显示,改进后的YOLOv7-Tiny在识别精度和效率方面明显提升.通过对YOLOv7-Tiny进行针对性的优化,可以显著提升变电设备红外图像的故障检测能力,为电力系统的稳定运行提供更可靠的技术支持.
Abstract
The original YOLOv7-Tiny faces the problems of insufficient recognition accuracy and slow processing speed when processing infrared images of substation equipment.To address these issues,a new model adjustment strategy was introduced and the performance of the algorithm before and after improvement was compared on a standard infrared image dataset.The results show that the improved YOLOv7-Tiny has significantly improved recognition accuracy and efficiency.By targeted optimization of YOLOv7-Tiny,the fault detection capability of infrared images of substation equipment can be significantly improved,providing more reliable technical support for the stable operation of the power system.
关键词
改进YOLOv7-Tiny技术/变电设备/红外图像识别系统Key words
improved YOLOv7-Tiny technology/substation equipment/infrared image recognition system引用本文复制引用
出版年
2024
NETL
NSTL
万方数据