YOLOv8改进策略在焊接外部缺陷检测模型中的应用研究

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中图分类号：TP391.4；TP183 文献标识码：A 文章编号：2096-4706（2025）12-0068-06

Research on the Application of YOLOv8 Improvement Strategy in Welding External Defect Detection Model

ZHU Yonghong，YANG Kaifu （Jingdezhen Ceramic University，Jingdezhen 333403，China）

Abstract： Aiming at the challenges of missed detection，false detection and arbitrary distribution of defect angles in smalltargetdefectdetectioninwelding extemaldefectimagedetection，anoptimizedand improvedmodelbasedonYOLOv8， YOLO-weld，isproposed.FirstlySPF-weldandC2f_DBB_CBAMmodulesaredesigned tonhancethecontextinfoation agregationabilityandmulti-scale featurefusioneffectofYOLO-weldmodel.Secondly，theOBBdetectionheadisintroduced toaccuratelycapturedirectionaldefects，soastoimprovethedetectionacuracy.Finalytheexperimentalresultshowthat compared with the YOLOv8 model， the YOLO-weld model improves the accuracy，recall，harmonic mean （F1） and mAP @0.5 by 3.2% 0 2.6% 0 4.0% and 3.9% ，respectively，which fully proves the effectiveness of the YOLO-weld model improvement.

Keywords： welding external defect identification; non-destructive testing; YOLOv8; C2f_DBB

0 引言

随着现代工业的迅猛发展，焊接技术已在众多工业领域中发挥着不可或缺的作用，保障焊接结构的坚固性和稳定性，已成为工业发展中的关键议题。（剩余8290字）