With the rapid expansion of the scale of the power grid, the efficiency of fault diagnosis has been severely challenged by the large amount of inspection image data generated by intelligent devices such as drones and inspection robots. In order to improve the efficiency of fault diagnosis for power equipment in substations, a new method for intelligently diagnosing different types of faults in power equipment is proposed. For circuit breakers and insulators, YOLOv4 is selected as the target detection model. To improve the detection performance of the YOLOv4 model, this paper improves it: the Cross Stage Partial (CSP) structure is introduced in the Spatial Pyramid Pooling (SPP) module of the neck of the YOLOv4 model. The experimental results show that after using the optimal learning rate decay strategy, the mAP and frames per second (FPS) of the improved YOLOv4 model are better than the original YOLOv4 and PP-YOLO model. Finally, an intelligent diagnosis terminal system for power equipment faults is developed. Through the target recognition and rapid extraction of equipment temperature, the intelligent diagnosis of thermal faults of equipment is realized. This method is especially suitable for accurate fault diagnosis of more power equipment, and has potential huge applicability in the field of power equipment diagnosis. © 2022 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.

中文翻译：

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基于单级红外图像目标检测的电力设备故障智能诊断方法

随着电网规模的快速扩张，无人机、巡检机器人等智能设备产生的海量巡检图像数据严重挑战了故障诊断的效率。为提高变电站电力设备故障诊断效率，提出一种智能诊断电力设备不同类型故障的新方法。对于断路器和绝缘子，选择YOLOv4作为目标检测模型。为了提高YOLOv4模型的检测性能，本文对其进行了改进：在YOLOv4模型颈部的Spatial Pyramid Pooling（SPP）模块中引入了Cross Stage Partial（CSP）结构。实验结果表明，使用最优学习率衰减策略后，改进后的 YOLOv4 模型的 mAP 和每秒帧数（FPS）优于原始 YOLOv4 和 PP-YOLO 模型。最后，开发了电力设备故障智能诊断终端系统。通过对设备温度的目标识别和快速提取，实现设备热故障的智能诊断。该方法特别适用于更多电力设备的准确故障诊断，在电力设备诊断领域具有潜在的巨大应用价值。© 2022 日本电气工程师学会。由 Wiley Periodicals LLC 出版。实现了设备热故障的智能诊断。该方法特别适用于更多电力设备的准确故障诊断，在电力设备诊断领域具有潜在的巨大应用价值。© 2022 日本电气工程师学会。由 Wiley Periodicals LLC 出版。实现了设备热故障的智能诊断。该方法特别适用于更多电力设备的准确故障诊断，在电力设备诊断领域具有潜在的巨大应用价值。© 2022 日本电气工程师学会。由 Wiley Periodicals LLC 出版。