基于改进U-Net的白车身焊点定位研究

Welding Spot Positioning Method for Body in White Based on Improved U‑Net

针对汽车白车身生产车间环境恶劣,光污染严重,视觉系统与其他装备相结合检测白车身焊点质量时难以准确定位、效率低下的问题,提出了一种改进U-Net的焊点分割算法。通过改进卷积结构更好地融合特征层语义信息,减轻网络结构;然后改进损失函数,融入注意力机制,在正负样本不均匀的情况下更好地挖掘前景,以获取不同尺度的空间特征并建立长期的通道关系。与原始的U-Net网络相比,所提RPSA-U-Net网络的Dice系数提高了8.76%,达到0.9836,MIOU提高了11.5%,达到0.9678,网络参数量减少7%。再结合图像处理方法找到焊点中心位置,效率和精度更高,具有应用价值。

Aiming at the harsh environment and serious light pollution in the production workshop of automobile body-in-white,it is difficult to accurately locate and inefficient when the vision system and other equipment are combined to detect the quality of the solder joints.An improved U-Net image segmentation algorithm was proposed.By improving the convolution structure to better fuse the semantic information of the feature map and lighten the network structure.Improve the loss function and integrate the attention mechanism to better mine the foreground in the case of uneven positive and negative samples,obtain spatial features of different scale feature maps and establish long-term channel relationships.Compared with the original U-Net network,the Dice coefficient of the proposed RPSA-U-Net network is increased by 8.76% to 0.9836,the MIOU is increased by 11.5% to 0.96781,and the network parameters are also reduced by 7%.Combined with the image processing method to find the center of the solder joint,the efficiency is higher and the precision is higher,and it has application value.