机械与电子2026，Vol.44Issue(7)：53-60,70,9.
基于融合残差门控重建的轴承缺陷检测算法研究
Research on Bearing Defect Detection Algorithm Based on Fused Residual Gated Reconstruction
摘要
Abstract
To address the issues of small defect features being easily overwhelmed by background clut-ter and inaccurate localization of complex morphologies in bearing surface defect detection,an improved YOLOv12 algorithm is proposed.A residual-gated spatial-channel reconstruction module is introduced to adaptively adjust the fusion intensity,thereby enhancing the perception of small defects.The regression loss is formulated as a weighted combination of SIoU and CIoU,which synergistically optimizes angular and shape attributes while balancing directional sensitivity and irregular localization.The proposed model achieves 88.6%mAP50 and 64.2%mAP95 with only 2 546 035 parameters and 6.1 GFLOPs,outperfor-ming the baseline YOLOv12n by 2.6 percentage points and 2.1 percentage points,respectively.With a comparable or even smaller model scale,the proposed method obtains higher detection accuracy than the small versions of YOLOv8s,YOLOv11s,and YOLOv12s,as well as RT-DETR and Deformable-DETR,while maintaining exceptionally high computational efficiency.关键词
轴承表面缺陷检测/YOLOv12/残差门控空间-通道重建模块/SIoU-CIoU组合损失Key words
bearing surface defect detection/YOLOv12/residual-gated spatial-channel reconstruction module/SIoU-CIoU combined loss分类
机械制造引用本文复制引用
王勇,刘献泓,刘盛,周丹,汤志伟,周锋..基于融合残差门控重建的轴承缺陷检测算法研究[J].机械与电子,2026,44(7):53-60,70,9.基金项目
江苏省特检院资助项目(KJ(Y)202633) （KJ(Y）
盐城市重点研发计划工业领域竞争资助项目(YCBG2024023) （YCBG2024023）
盐城市应用基础研究计划资助项目(YCBK2025007) （YCBK2025007）
江苏省研究生科研与实践创新计划资助项目(SJCX24_2153,SJCX25_2202) （SJCX24_2153,SJCX25_2202）
