基于改进YOLOv5的变电站室外仪表检测算法

Xiaoqiang Fan, Yong Jiang
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引用次数: 0

摘要

随着变电站巡检机器人的日益普及,室外巡检图片的定位与检测逐渐成为研究的重点和难点。对于室外变电站电表,在不同的天气条件下,针对现阶段检测算法模型复杂度高、容易检测到目标导致识别率低、不利于快速部署实际应用等问题,提出了一种改进的基于YOLOv5的变电站检测算法,该算法采用YOLOv5 + CBAM注意机制模块对电表表盘进行检测;算法采用YOLOv5+CBAM注意机制模块对仪表表盘进行检测,对于在不同天气条件下准确、快速识别仪表表盘,进一步实现变电站智能化巡检具有重要意义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Substation outdoor instrumentation detection algorithm based on improved YOLOv5
With the increasing popularity of substation inspection robots, the localization and detection of outdoor inspection pictures gradually becomes the focus and difficulty of research. For outdoor substation meters, in different weather conditions, for the current stage of detection algorithm model complexity is high, easy to the detection of the target caused by low recognition rate, is not conducive to the rapid deployment of practical applications and other problems, proposed an improved YOLOV5-based substation detection algorithm, the algorithm uses YOLOv5 + CBAM attention mechanism module to detect meter dials, for different weather conditions The algorithm uses YOLOv5+CBAM attention mechanism module to detect meter dials, which is of great significance to identify meter dials accurately and quickly under different weather conditions and further realize intelligent inspection of substations.
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