During the post-processing of PIV images,correction of their error vectors plays a key role in obtaining accurate velocity vector fields.In this study,the error vectors were artificially added to the simulated and experimental vector map database,and the Deeplab v3+algorithm was used to identify the segmented error vectors by annotating the added error vectors images and generating the mask(mask)for correction at the same time,and the loss of its identification segmentation was controlled at 0.001.For the repair,the DeepFill v2 algorithm was used to train the network with the correct vector images to stabilize the loss at 0.05.The recognition of the generated mask and the original PIV image to be corrected are put into the corrected image,and the automatic recognition and correction of error vectors in the PIV vector image can be achieved by inputting commands.The results show that this method,which can batch process PIV vector images,is simple,convenient and automatic,and has high recognition segmentation and correction accuracy.
PIV vector imagesdeep learningfalse vector recognition and repairdeeplab v3+DeepFill v2
NETL
NSTL
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