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    • 改进的Faster-RCNN算法在聚乙烯管接头内部缺陷检测中的应用

    PENG Yijuan,WANG Zhenchao,ZHANG Qiuju

    Journal of Applied Acoustics（2023）

    江南大学 | 江南大学机械工程学院 无锡 214122

    Cited 0|Views2
    Abstract
    超声相控阵技术是目前聚乙烯管道热熔接头内部缺陷检测的一种主流方法.提出了基于注意力机制的改进Faster-RCNN目标检测网络用于超声相控阵D扫图聚乙烯管接头内部缺陷检测.针对聚乙烯管道热熔接头内部超声相控阵D扫图小缺陷较多、特征信息容易丢失的问题,将残差网络(ResNet50)与特征金字塔网络(FPN)相结合作为骨干网络,并引入卷积注意力模块(CBAM)自适应细化特征.将SSD网络框架和Faster-RCNN 网络框架用于模型训练和测试,使用 VGG16、ResNet50、ResNet50+FPN、ACBM+ResNet50+FPN作为骨干网络依次对超声相控阵聚乙烯管道热熔对接接头内部缺陷样本进行训练对比.结果表明,改进的Faster-RCNN网络模型在聚乙烯管接头内部缺陷检测和分类方面有明显改进,对小缺陷的检测性能有了显著的提高.
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    Key words
    Defect detecting,Ultrasonic phased array,Convolutional block attention module,Residual net-work,Feature pyramid
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