Intelligent evaluation of X-ray crack image of aircraft structure

Abstract

In the process of aircraft structure X-ray images evaluation，there are some problems such as inaccurate crack segmentation and difficult crack detection under complex background. An intelligent evaluation model （ELAN-Seg） for X-ray crack images of aircraft structures is proposed based on efficient layer aggregation network. The ELAN-Seg model is compared with the DeepLabv3+ model in the crack segmentation ability of the Xray images. Combined with image processing technology，the crack length of model segmentation is evaluated，and the model is verified by X-ray images acquired during aircraft strength test and field maintenance. The results show that the segmented minimum crack length is about 3 mm，the ELAN-Seg model is more accurate in crack segmentation of complex background X-ray images，and the crack detection rate is less than 3.8%. The proposed model has engineering applicability.

Keywords

• x-ray
• crack image
• efficient layer aggregation network
• attention mechanism
• intelligent evaluation