Casting Internal Defect Detection Method Based on Bidirectional Weighted Feature Fusion Network
Aiming at the problems of small internal defects,weak contrast and low efficiency of manual recognition in the process of X-ray nondestructive testing,a method of casting internal defects detection based on bi-weighted feature fusion network was proposed.Based on the YOLOv5 network model,an improved coordinate attention module(NCA)was introduced to improve the learning ability of the network for irregular defects and minor defects.Bidirectional feature pyramid network(BiFPN)was introduced to replace the original path aggregation network(PANet)to achieve multi-scale efficient fusion of defect features,and EIoU Loss regression loss function was used to improve the accuracy of defect boundary frame location.The experimental results showed that the proposed method had good performance in detecting small targets and weak contrast defects in the castings.
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