Bidirectional target tracking model for aircraft structural fatigue crack length monitoring

Crack length measurement algorithms based on computer vision have shown promising engineering application prospects in the field of aircraft fatigue crack monitoring. However, due to the complexity of the monitoring environment, the subtle visual features of small fatigue cracks, and the impact of structural elastic deformation, directly applying object segmentation algorithms often results in significant measurement errors. Therefore, this paper proposes a high-precision crack length measurement method based on Bidirectional Target Tracking Model (Bi2TM), which integrates crack tip localization, interference identification, and length compensation. First, a general object segmentation model is used to perform rough crack segmentation. Then, the Bi2TM network, combined with the visual features of the structure in different stress states, is employed to track the bidirectional position of the crack tip in the “open” and “closed” states. This ultimately enables interference identification within the rough segmented crack region, achieving high-precision length measurement. In a high-interference environment of aircraft fatigue testing, the proposed method is used to measure 1000 crack images ranging from 1 mm to 11 mm. For more than 90% of the samples, the measurement error is less than 5 pixels, demonstrating significant advantages over the existing methods.