| Citation: | Wang Yanfei, Zhang Yinlong, Liu Zhangbo, et al. Borescope vision-based aero-engine blade counting method[J]. Journal of Aerospace Power, 2026, 41（7）：20240665 doi: 10.13224/j.cnki.jasp.20240665
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Blades counting in aero-engines based on borescope vision is a critical component of routine maintenance. However, factors such as surface reflections and posture variations pose significant challenges to the real-time accuracy of existing blade counting methods. To address these challenges, a blade counting methods based on edge detection was proposed. To achieve efficient and accurate blade detection, an enhanced blade detection transformer (EB-DETR) model, augmented by the GS-ECA module, was presented to significantly enhance the representation and extraction efficiency of blade features. Furthermore, an innovative temporal-spatial correlation state machine (TSCSM) model was introduced for effectively capturing the temporal and spatial information of blade edge feature points for counting blades in aero-engines. Experimental results demonstrated that the proposed EB-DETR model achieved an average precision (AP50) of 93.17%, reflecting a 6.54% improvement over other state-of-the-art (SOTA) models of similar scale, while reducing Giga floating point operations (GFLOPs) by 35.16% and achieving a detection speed of 61 frames per second (FPS). Additionally, the mean counting precision (MCP) for blades in aero-engines reached 97.06%, exceeding existing blade counting methods by 45.82%, thus satisfying the practical requirements for blade counting in aero-engines.
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