YOLOv4-based Surface Defect Detection of Low-voltage Distribution Box
The current conventional detection method of surface defects for low-voltage distribution boxes mainly uses infrared sensing equipment to scan the surface to achieve defect detection,which leads to poor detection accuracy due to the lack of fusion processing of defect features.In this regard,a YOLOv4 algorithm-based detection method for low-voltage distribution box surface defects is proposed.First the original image is grayed out and the Gaussian filtering algorithm is used to reduce noise part in the image.Then by constructing a CNN network structure,defect edge features in the image are separated,and the multi-feature fu-sion is realized by fitting the feature extraction results.Finally,by constructing the YOLOv4 network structure,the activation function and attention mechanism are designed to localize and detect surface defects.The proposed method is verified by perform-ance test to have low vertical depth detection error and higher accuracy.
distribution boxdefect detectionYOLOv4defect location
NETL
NSTL
万方数据
维普
