Abstract
Time-of-flight diffraction (TOFD) has become a widely used nondestructive testing (NDT) technique, owing to its wide coverage, fast detection speeds, and high defect detection rates. However, compared with nondestructive radiographic testing images, TOFD image analysis requires more technicians and more difficult defect analysis. Owing to the improvements in weld manufacturing quality, there are fewer welds with defects; consequently, a large number of TOFD images have no defect information. The TOFD image analysis of normal welds occupies a lot of time in the weld evaluation process that easily leads to problems of missed and false detections and reduces the efficiency of overall weld evaluation. To solve these problems, a TOFD image reconstruction model based on the generative adversarial network (GAN) and a normal weld recognition method are proposed. First, combined with the TOFD image characteristics, an image-wave feature fusion (IWFF) module based on depth-separable convolution is designed, which integrates and analyzes the TOFD image and wave features, and an IWFF–GAN model is developed. Second, to improve the accuracy of normal weld recognition, a method for denoising the reconstructed error-feature map based on the total variation model is proposed. Finally, the proposed method is verified using the TOFD images of large-scale spherical pressure-tank welds. The results show that the method accurately distinguishes between the normal and abnormal welds, exhibiting a higher normal weld recognition accuracy. The area under the receiver operating characteristic curve is 0.9903.
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Funding
This paper was supported by the National Key Research and Development Program of China (SQ2021YFF0600205) and the Research and Development Project of the TOFD Auxiliary Recognition System for Detecting Weld Defects in Spherical Tank (SXTJKJXM-202003). The funder had no role in experimental design, model establishment, data analysis, manuscript writing, or decisions to submit articles for publication.
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Jiang, H., Yang, D., Zhi, Z. et al. A normal weld recognition method for time-of-flight diffraction detection based on generative adversarial network. J Intell Manuf 35, 217–233 (2024). https://doi.org/10.1007/s10845-022-02041-9
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DOI: https://doi.org/10.1007/s10845-022-02041-9