Method of insulator defect detection based on the improved YOLOv5s

Rui Yang

doi:10.1117/12.3004942

16 August 2023 Method of insulator defect detection based on the improved YOLOv5s

Rui Yang

Proceedings Volume 12787, Sixth International Conference on Advanced Electronic Materials, Computers, and Software Engineering (AEMCSE 2023); 1278729 (2023) https://doi.org/10.1117/12.3004942
Event: 6th International Conference on Advanced Electronic Materials, Computers and Software Engineering (AEMCSE 2023), 2023, Shenyang, China

Abstract

Aiming at the problem of low accuracy in detecting small defects in insulator aerial images using the current YOLOv5s target detection network, this paper designs an insulator defect detection algorithm based on improved YOLOv5s. Firstly, in the feature extraction stage, a PST attention module is embedded to suppress redundant interfering feature information; The guidance network grasps effective features for learning during the training process. Secondly, a feature fusion module with a bilateral structure is used in the feature fusion process, making full use of contextual semantic information to improve the accuracy of small-scale target detection. The experimental results show that the average accuracy of the improved YOLOv5 algorithm is 81.82%, which is 4.71 percentage points higher than YOLOv5s algorithm and 1.2 percentage points higher than YOLOX-S. This indicates that the improved YOLOv5s network model used in this paper has good results in the detection of insulator defects and has certain application value in actual power inspection tasks.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Rui Yang "Method of insulator defect detection based on the improved YOLOv5s", Proc. SPIE 12787, Sixth International Conference on Advanced Electronic Materials, Computers, and Software Engineering (AEMCSE 2023), 1278729 (16 August 2023); https://doi.org/10.1117/12.3004942

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KEYWORDS

Detection and tracking algorithms

Defect detection

Feature fusion

Education and training

Feature extraction

Semantics

Target detection

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